Se cargan las librerías a utilizar para el presente análisis
## This is lavaan 0.6-6
## lavaan is BETA software! Please report any bugs.
data1 <- haven::read_sav("1. BD/BD_1ER ENVIO.sav")
data2 <- haven::read_sav("1. BD/BD_Colegio Jose Granda.sav")Se guardan las etiquetas asociadas a los datos provenientes de la codificación en el SPSS
Se juntan las 2 base de datos. Además se elimina data missing y se transforma los ítems a variables númericas (para fines de análisis).
data1 <- data1 %>%
select(Cedula, Sexo:Cadri35b) %>%
mutate(Colegio = "Colegio Independencia")
data2 <- data2 %>%
select(Cedula, Colegio:Cadri35b)
cadri_data <- rbind(data1, data2)
cadri_data <- cadri_data %>%
drop_na(Cadri1a:Cadri35b)
cadri_data <- cadri_data %>%
mutate(across(Cadri1a:Cadri35b, as.numeric))Estadísticos descriptivos para la parte “a” de los ítems (perpetrador)
descriptivos_a <- cadri_data %>%
select(ends_with("a") & starts_with("Cadri")) %>%
psych::describe() %>%
mutate_if(is.numeric, round, 3)Estadísticos descriptivos para la parte “b” de los ítems (violencia sufrida)
descriptivos_b <- cadri_data %>%
select(ends_with("b") & starts_with("Cadri")) %>%
psych::describe() %>%
mutate_if(is.numeric, round, 3)Visualización de los descriptivos a y b
cadri_data %>%
select(ends_with("a") & starts_with("Cadri")) %>%
pivot_longer(
cols = everything(),
names_to = "Items",
values_to = "Puntaje"
) %>%
mutate(
Items = as_factor(Items),
Puntaje = factor(Puntaje,
levels = c(4, 3, 2, 1),
labels = c("6 o más veces",
"3 a 5 veces",
"1 a 2 veces",
"Nunca"))
) %>%
count(Items, Puntaje) %>%
ggplot(aes(x = Puntaje, y = n)) +
geom_col() +
coord_flip() +
facet_wrap(~ Items) +
labs(title = "Descriptivo de los ítems del CADRI - Violencia Cometida",
y = "",
x = "Participantes") +
theme_bw()cadri_data %>%
select(ends_with("b") & starts_with("Cadri")) %>%
pivot_longer(
cols = everything(),
names_to = "Items",
values_to = "Puntaje"
) %>%
mutate(
Items = as_factor(Items),
Puntaje = factor(Puntaje,
levels = c(4, 3, 2, 1),
labels = c("6 o más veces",
"3 a 5 veces",
"1 a 2 veces",
"Nunca"))
) %>%
count(Items, Puntaje) %>%
ggplot(aes(x = Puntaje, y = n)) +
geom_col() +
coord_flip() +
facet_wrap(~ Items) +
labs(title = "Descriptivo de los ítems del CADRI - Violencia Recibida",
y = "",
x = "Participantes") +
theme_bw()La escala CADRI tiene 5 factores y se corresponden con los items de la siguiente manera:
Nota: Todos los modelos tienen 2 análisis fit_a y fit_b que se diferencian únicamente por el estimador utilizado para su evaluación. El fit_a utiliza el estimador MLR que es ideal para data contínua y problemas de normalidad, mientras que el fit_b utiliza el estimador WLSMVque es el mejor estimador en consideración de la ordinalidad de los datos.
El primer modelo probará todos los ítems tal cual se encuentran descritos en el instrumento original.
model01 <- "# Modelo de medición
V_verbal =~ Cadri4a + Cadri7a + Cadri9a + Cadri12a + Cadri17a + Cadri21a + Cadri23a +
Cadri24a + Cadri28a + Cadri32a
V_fisica =~ Cadri8a + Cadri25a + Cadri30a + Cadri34a
C_amenaz =~ Cadri5a + Cadri29a + Cadri31a + Cadri33a
V_relaci =~ Cadri3a + Cadri20a + Cadri35a
V_sexual =~ Cadri2a + Cadri13a + Cadri15a + Cadri19a
R_confli =~ Cadri1a + Cadri6a + Cadri10a + Cadri11a + Cadri14a + Cadri16a + Cadri18a +
Cadri22a + Cadri26a + Cadri27a"## Warning in lav_object_post_check(object): lavaan WARNING: covariance matrix of latent variables
## is not positive definite;
## use lavInspect(fit, "cov.lv") to investigate.
## lavaan 0.6-6 ended normally after 212 iterations
##
## Estimator ML
## Optimization method NLMINB
## Number of free parameters 85
##
## Number of observations 326
##
## Model Test User Model:
## Standard Robust
## Test Statistic 1586.734 1328.504
## Degrees of freedom 545 545
## P-value (Chi-square) 0.000 0.000
## Scaling correction factor 1.194
## Yuan-Bentler correction (Mplus variant)
##
## Model Test Baseline Model:
##
## Test statistic 4556.896 3264.743
## Degrees of freedom 595 595
## P-value 0.000 0.000
## Scaling correction factor 1.396
##
## User Model versus Baseline Model:
##
## Comparative Fit Index (CFI) 0.737 0.707
## Tucker-Lewis Index (TLI) 0.713 0.680
##
## Robust Comparative Fit Index (CFI) 0.749
## Robust Tucker-Lewis Index (TLI) 0.726
##
## Loglikelihood and Information Criteria:
##
## Loglikelihood user model (H0) -7788.654 -7788.654
## Scaling correction factor 6.652
## for the MLR correction
## Loglikelihood unrestricted model (H1) -6995.286 -6995.286
## Scaling correction factor 1.931
## for the MLR correction
##
## Akaike (AIC) 15747.307 15747.307
## Bayesian (BIC) 16069.194 16069.194
## Sample-size adjusted Bayesian (BIC) 15799.579 15799.579
##
## Root Mean Square Error of Approximation:
##
## RMSEA 0.077 0.066
## 90 Percent confidence interval - lower 0.072 0.062
## 90 Percent confidence interval - upper 0.081 0.071
## P-value RMSEA <= 0.05 0.000 0.000
##
## Robust RMSEA 0.073
## 90 Percent confidence interval - lower 0.068
## 90 Percent confidence interval - upper 0.078
##
## Standardized Root Mean Square Residual:
##
## SRMR 0.083 0.083
##
## Parameter Estimates:
##
## Standard errors Sandwich
## Information bread Observed
## Observed information based on Hessian
##
## Latent Variables:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## V_verbal =~
## Cadri4a 1.000 0.370 0.451
## Cadri7a 1.503 0.250 6.000 0.000 0.556 0.720
## Cadri9a 1.141 0.174 6.550 0.000 0.422 0.549
## Cadri12a 1.230 0.257 4.784 0.000 0.455 0.646
## Cadri17a 1.075 0.214 5.025 0.000 0.398 0.696
## Cadri21a 0.627 0.188 3.334 0.001 0.232 0.477
## Cadri23a 0.377 0.097 3.870 0.000 0.139 0.330
## Cadri24a 0.938 0.200 4.694 0.000 0.347 0.603
## Cadri28a 1.352 0.230 5.885 0.000 0.500 0.633
## Cadri32a 1.252 0.235 5.320 0.000 0.463 0.667
## V_fisica =~
## Cadri8a 1.000 0.268 0.720
## Cadri25a 0.780 0.245 3.178 0.001 0.209 0.586
## Cadri30a 1.103 0.241 4.567 0.000 0.296 0.694
## Cadri34a 0.847 0.207 4.085 0.000 0.227 0.624
## C_amenaz =~
## Cadri5a 1.000 0.061 0.224
## Cadri29a 1.697 1.425 1.191 0.234 0.103 0.268
## Cadri31a 1.412 0.887 1.592 0.111 0.086 0.390
## Cadri33a 2.609 1.601 1.629 0.103 0.159 0.592
## V_relaci =~
## Cadri3a 1.000 0.116 0.295
## Cadri20a 1.690 1.082 1.562 0.118 0.195 0.575
## Cadri35a 1.772 1.343 1.319 0.187 0.205 0.523
## V_sexual =~
## Cadri2a 1.000 0.166 0.368
## Cadri13a 0.490 0.593 0.826 0.409 0.081 0.469
## Cadri15a 0.530 0.564 0.938 0.348 0.088 0.652
## Cadri19a 1.779 0.991 1.795 0.073 0.296 0.381
## R_confli =~
## Cadri1a 1.000 0.663 0.633
## Cadri6a 0.887 0.074 12.048 0.000 0.588 0.644
## Cadri10a 0.968 0.089 10.903 0.000 0.642 0.669
## Cadri11a 0.909 0.075 12.047 0.000 0.603 0.664
## Cadri14a 1.171 0.098 11.906 0.000 0.777 0.759
## Cadri16a 1.094 0.101 10.824 0.000 0.726 0.720
## Cadri18a 1.152 0.102 11.343 0.000 0.764 0.735
## Cadri22a 1.014 0.107 9.472 0.000 0.672 0.639
## Cadri26a 1.032 0.100 10.327 0.000 0.684 0.689
## Cadri27a 0.732 0.090 8.138 0.000 0.486 0.512
##
## Covariances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## V_verbal ~~
## V_fisica 0.061 0.021 2.925 0.003 0.617 0.617
## C_amenaz 0.016 0.008 1.952 0.051 0.709 0.709
## V_relaci 0.033 0.022 1.498 0.134 0.774 0.774
## V_sexual 0.025 0.025 0.984 0.325 0.406 0.406
## R_confli 0.098 0.023 4.188 0.000 0.401 0.401
## V_fisica ~~
## C_amenaz 0.017 0.008 2.058 0.040 1.014 1.014
## V_relaci 0.009 0.011 0.801 0.423 0.287 0.287
## V_sexual 0.022 0.024 0.938 0.348 0.498 0.498
## R_confli 0.026 0.010 2.483 0.013 0.144 0.144
## C_amenaz ~~
## V_relaci 0.005 0.006 0.815 0.415 0.712 0.712
## V_sexual 0.003 0.006 0.473 0.636 0.289 0.289
## R_confli 0.007 0.007 1.056 0.291 0.171 0.171
## V_relaci ~~
## V_sexual 0.003 0.009 0.386 0.700 0.176 0.176
## R_confli 0.015 0.011 1.404 0.160 0.195 0.195
## V_sexual ~~
## R_confli 0.023 0.030 0.745 0.456 0.205 0.205
##
## Variances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .Cadri4a 0.537 0.057 9.407 0.000 0.537 0.797
## .Cadri7a 0.287 0.032 8.857 0.000 0.287 0.481
## .Cadri9a 0.413 0.048 8.535 0.000 0.413 0.699
## .Cadri12a 0.288 0.042 6.809 0.000 0.288 0.582
## .Cadri17a 0.168 0.023 7.336 0.000 0.168 0.516
## .Cadri21a 0.183 0.034 5.367 0.000 0.183 0.773
## .Cadri23a 0.159 0.041 3.907 0.000 0.159 0.891
## .Cadri24a 0.210 0.023 9.108 0.000 0.210 0.636
## .Cadri28a 0.373 0.042 8.906 0.000 0.373 0.599
## .Cadri32a 0.267 0.038 7.105 0.000 0.267 0.555
## .Cadri8a 0.067 0.015 4.582 0.000 0.067 0.481
## .Cadri25a 0.084 0.021 3.904 0.000 0.084 0.657
## .Cadri30a 0.094 0.033 2.877 0.004 0.094 0.519
## .Cadri34a 0.081 0.024 3.350 0.001 0.081 0.611
## .Cadri5a 0.070 0.031 2.300 0.021 0.070 0.950
## .Cadri29a 0.138 0.027 5.131 0.000 0.138 0.928
## .Cadri31a 0.041 0.025 1.617 0.106 0.041 0.848
## .Cadri33a 0.047 0.025 1.855 0.064 0.047 0.649
## .Cadri3a 0.140 0.045 3.087 0.002 0.140 0.913
## .Cadri20a 0.077 0.031 2.462 0.014 0.077 0.669
## .Cadri35a 0.111 0.031 3.569 0.000 0.111 0.726
## .Cadri2a 0.176 0.056 3.118 0.002 0.176 0.864
## .Cadri13a 0.023 0.010 2.337 0.019 0.023 0.780
## .Cadri15a 0.011 0.011 0.991 0.322 0.011 0.576
## .Cadri19a 0.513 0.154 3.326 0.001 0.513 0.855
## .Cadri1a 0.657 0.058 11.270 0.000 0.657 0.599
## .Cadri6a 0.489 0.048 10.089 0.000 0.489 0.586
## .Cadri10a 0.509 0.051 9.926 0.000 0.509 0.553
## .Cadri11a 0.461 0.048 9.579 0.000 0.461 0.559
## .Cadri14a 0.444 0.050 8.848 0.000 0.444 0.424
## .Cadri16a 0.489 0.055 8.859 0.000 0.489 0.482
## .Cadri18a 0.497 0.053 9.427 0.000 0.497 0.460
## .Cadri22a 0.654 0.067 9.756 0.000 0.654 0.591
## .Cadri26a 0.517 0.056 9.202 0.000 0.517 0.525
## .Cadri27a 0.663 0.053 12.462 0.000 0.663 0.738
## V_verbal 0.137 0.041 3.346 0.001 1.000 1.000
## V_fisica 0.072 0.032 2.231 0.026 1.000 1.000
## C_amenaz 0.004 0.004 0.964 0.335 1.000 1.000
## V_relaci 0.013 0.016 0.847 0.397 1.000 1.000
## V_sexual 0.028 0.026 1.068 0.285 1.000 1.000
## R_confli 0.440 0.065 6.791 0.000 1.000 1.000
fit01_b <- cfa(model = model01,
data = cadri_data,
ordered = TRUE,
estimator = "WLSMV",
mimic = "Mplus")## Warning in lav_model_vcov(lavmodel = lavmodel, lavsamplestats = lavsamplestats, : lavaan WARNING:
## The variance-covariance matrix of the estimated parameters (vcov)
## does not appear to be positive definite! The smallest eigenvalue
## (= -4.850446e-17) is smaller than zero. This may be a symptom that
## the model is not identified.
## Warning in lav_object_post_check(object): lavaan WARNING: some estimated ov
## variances are negative
## Warning in lav_object_post_check(object): lavaan WARNING: covariance matrix of latent variables
## is not positive definite;
## use lavInspect(fit, "cov.lv") to investigate.
## lavaan 0.6-6 ended normally after 61 iterations
##
## Estimator DWLS
## Optimization method NLMINB
## Number of free parameters 151
##
## Number of observations 326
##
## Model Test User Model:
## Standard Robust
## Test Statistic 1256.588 938.927
## Degrees of freedom 545 545
## P-value (Chi-square) 0.000 0.000
## Scaling correction factor 2.187
## Shift parameter 364.337
## simple second-order correction (WLSMV)
##
## Model Test Baseline Model:
##
## Test statistic 19668.362 6040.324
## Degrees of freedom 595 595
## P-value 0.000 0.000
## Scaling correction factor 3.503
##
## User Model versus Baseline Model:
##
## Comparative Fit Index (CFI) 0.963 0.928
## Tucker-Lewis Index (TLI) 0.959 0.921
##
## Robust Comparative Fit Index (CFI) NA
## Robust Tucker-Lewis Index (TLI) NA
##
## Root Mean Square Error of Approximation:
##
## RMSEA 0.063 0.047
## 90 Percent confidence interval - lower 0.059 0.042
## 90 Percent confidence interval - upper 0.068 0.052
## P-value RMSEA <= 0.05 0.000 0.819
##
## Robust RMSEA NA
## 90 Percent confidence interval - lower NA
## 90 Percent confidence interval - upper NA
##
## Standardized Root Mean Square Residual:
##
## SRMR 0.190 0.190
##
## Weighted Root Mean Square Residual:
##
## WRMR 1.344 1.344
##
## Parameter Estimates:
##
## Standard errors Robust.sem
## Information Expected
## Information saturated (h1) model Unstructured
##
## Latent Variables:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## V_verbal =~
## Cadri4a 1.000 0.602 0.602
## Cadri7a 1.288 0.105 12.273 0.000 0.776 0.776
## Cadri9a 1.123 0.101 11.078 0.000 0.676 0.676
## Cadri12a 1.187 0.111 10.669 0.000 0.715 0.715
## Cadri17a 1.309 0.116 11.327 0.000 0.788 0.788
## Cadri21a 1.006 0.123 8.149 0.000 0.606 0.606
## Cadri23a 0.870 0.122 7.147 0.000 0.524 0.524
## Cadri24a 1.171 0.095 12.350 0.000 0.705 0.705
## Cadri28a 1.229 0.107 11.471 0.000 0.740 0.740
## Cadri32a 1.128 0.098 11.458 0.000 0.680 0.680
## V_fisica =~
## Cadri8a 1.000 0.839 0.839
## Cadri25a 0.981 0.082 12.005 0.000 0.823 0.823
## Cadri30a 1.014 0.088 11.535 0.000 0.851 0.851
## Cadri34a 0.972 0.081 12.044 0.000 0.816 0.816
## C_amenaz =~
## Cadri5a 1.000 0.546 0.546
## Cadri29a 1.120 0.174 6.445 0.000 0.611 0.611
## Cadri31a 1.256 0.238 5.281 0.000 0.686 0.686
## Cadri33a 1.589 0.241 6.584 0.000 0.868 0.868
## V_relaci =~
## Cadri3a 1.000 0.610 0.610
## Cadri20a 1.323 0.225 5.888 0.000 0.807 0.807
## Cadri35a 1.135 0.186 6.093 0.000 0.693 0.693
## V_sexual =~
## Cadri2a 1.000 0.629 0.629
## Cadri13a 0.753 0.154 4.897 0.000 0.474 0.474
## Cadri15a 1.872 0.339 5.524 0.000 1.178 1.178
## Cadri19a 1.201 0.226 5.309 0.000 0.756 0.756
## R_confli =~
## Cadri1a 1.000 0.704 0.704
## Cadri6a 1.043 0.056 18.680 0.000 0.734 0.734
## Cadri10a 1.073 0.061 17.616 0.000 0.755 0.755
## Cadri11a 1.021 0.059 17.300 0.000 0.719 0.719
## Cadri14a 1.135 0.062 18.348 0.000 0.799 0.799
## Cadri16a 1.166 0.058 20.261 0.000 0.821 0.821
## Cadri18a 1.086 0.063 17.342 0.000 0.765 0.765
## Cadri22a 1.068 0.064 16.764 0.000 0.752 0.752
## Cadri26a 1.105 0.055 19.926 0.000 0.778 0.778
## Cadri27a 0.839 0.063 13.378 0.000 0.591 0.591
##
## Covariances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## V_verbal ~~
## V_fisica 0.375 0.045 8.322 0.000 0.741 0.741
## C_amenaz 0.300 0.054 5.515 0.000 0.913 0.913
## V_relaci 0.316 0.058 5.447 0.000 0.860 0.860
## V_sexual 0.158 0.036 4.391 0.000 0.416 0.416
## R_confli 0.220 0.030 7.420 0.000 0.518 0.518
## V_fisica ~~
## C_amenaz 0.464 0.073 6.351 0.000 1.011 1.011
## V_relaci 0.253 0.075 3.371 0.001 0.493 0.493
## V_sexual 0.268 0.052 5.169 0.000 0.508 0.508
## R_confli 0.152 0.041 3.728 0.000 0.257 0.257
## C_amenaz ~~
## V_relaci 0.269 0.061 4.430 0.000 0.808 0.808
## V_sexual 0.265 0.056 4.707 0.000 0.772 0.772
## R_confli 0.155 0.039 3.960 0.000 0.403 0.403
## V_relaci ~~
## V_sexual 0.242 0.062 3.937 0.000 0.631 0.631
## R_confli 0.132 0.042 3.119 0.002 0.307 0.307
## V_sexual ~~
## R_confli 0.150 0.046 3.242 0.001 0.339 0.339
##
## Intercepts:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .Cadri4a 0.000 0.000 0.000
## .Cadri7a 0.000 0.000 0.000
## .Cadri9a 0.000 0.000 0.000
## .Cadri12a 0.000 0.000 0.000
## .Cadri17a 0.000 0.000 0.000
## .Cadri21a 0.000 0.000 0.000
## .Cadri23a 0.000 0.000 0.000
## .Cadri24a 0.000 0.000 0.000
## .Cadri28a 0.000 0.000 0.000
## .Cadri32a 0.000 0.000 0.000
## .Cadri8a 0.000 0.000 0.000
## .Cadri25a 0.000 0.000 0.000
## .Cadri30a 0.000 0.000 0.000
## .Cadri34a 0.000 0.000 0.000
## .Cadri5a 0.000 0.000 0.000
## .Cadri29a 0.000 0.000 0.000
## .Cadri31a 0.000 0.000 0.000
## .Cadri33a 0.000 0.000 0.000
## .Cadri3a 0.000 0.000 0.000
## .Cadri20a 0.000 0.000 0.000
## .Cadri35a 0.000 0.000 0.000
## .Cadri2a 0.000 0.000 0.000
## .Cadri13a 0.000 0.000 0.000
## .Cadri15a 0.000 0.000 0.000
## .Cadri19a 0.000 0.000 0.000
## .Cadri1a 0.000 0.000 0.000
## .Cadri6a 0.000 0.000 0.000
## .Cadri10a 0.000 0.000 0.000
## .Cadri11a 0.000 0.000 0.000
## .Cadri14a 0.000 0.000 0.000
## .Cadri16a 0.000 0.000 0.000
## .Cadri18a 0.000 0.000 0.000
## .Cadri22a 0.000 0.000 0.000
## .Cadri26a 0.000 0.000 0.000
## .Cadri27a 0.000 0.000 0.000
## V_verbal 0.000 0.000 0.000
## V_fisica 0.000 0.000 0.000
## C_amenaz 0.000 0.000 0.000
## V_relaci 0.000 0.000 0.000
## V_sexual 0.000 0.000 0.000
## R_confli 0.000 0.000 0.000
##
## Thresholds:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## Cadri4a|t1 -0.069 0.070 -0.994 0.320 -0.069 -0.069
## Cadri4a|t2 1.035 0.085 12.173 0.000 1.035 1.035
## Cadri4a|t3 1.717 0.123 13.919 0.000 1.717 1.717
## Cadri7a|t1 0.178 0.070 2.539 0.011 0.178 0.178
## Cadri7a|t2 1.347 0.098 13.713 0.000 1.347 1.347
## Cadri7a|t3 1.717 0.123 13.919 0.000 1.717 1.717
## Cadri9a|t1 0.015 0.070 0.221 0.825 0.015 0.015
## Cadri9a|t2 1.177 0.090 13.029 0.000 1.177 1.177
## Cadri9a|t3 1.871 0.138 13.536 0.000 1.871 1.871
## Cadri12a|t1 0.549 0.074 7.465 0.000 0.549 0.549
## Cadri12a|t2 1.495 0.107 14.000 0.000 1.495 1.495
## Cadri12a|t3 1.871 0.138 13.536 0.000 1.871 1.871
## Cadri17a|t1 0.844 0.079 10.623 0.000 0.844 0.844
## Cadri17a|t2 1.654 0.118 14.003 0.000 1.654 1.654
## Cadri17a|t3 2.357 0.214 11.014 0.000 2.357 2.357
## Cadri21a|t1 1.089 0.087 12.530 0.000 1.089 1.089
## Cadri21a|t2 1.917 0.143 13.374 0.000 1.917 1.917
## Cadri21a|t3 2.357 0.214 11.014 0.000 2.357 2.357
## Cadri23a|t1 1.224 0.092 13.258 0.000 1.224 1.224
## Cadri23a|t2 2.088 0.166 12.614 0.000 2.088 2.088
## Cadri23a|t3 2.504 0.250 10.011 0.000 2.504 2.504
## Cadri24a|t1 0.445 0.072 6.162 0.000 0.445 0.445
## Cadri24a|t2 1.871 0.138 13.536 0.000 1.871 1.871
## Cadri24a|t3 2.357 0.214 11.014 0.000 2.357 2.357
## Cadri28a|t1 0.462 0.072 6.380 0.000 0.462 0.462
## Cadri28a|t2 1.177 0.090 13.029 0.000 1.177 1.177
## Cadri28a|t3 1.828 0.134 13.667 0.000 1.828 1.828
## Cadri32a|t1 0.622 0.075 8.324 0.000 0.622 0.622
## Cadri32a|t2 1.569 0.112 14.040 0.000 1.569 1.569
## Cadri32a|t3 1.828 0.134 13.667 0.000 1.828 1.828
## Cadri8a|t1 1.347 0.098 13.713 0.000 1.347 1.347
## Cadri8a|t2 2.161 0.177 12.220 0.000 2.161 2.161
## Cadri8a|t3 2.740 0.329 8.326 0.000 2.740 2.740
## Cadri25a|t1 1.257 0.094 13.400 0.000 1.257 1.257
## Cadri25a|t2 2.249 0.192 11.707 0.000 2.249 2.249
## Cadri30a|t1 1.257 0.094 13.400 0.000 1.257 1.257
## Cadri30a|t2 2.024 0.157 12.925 0.000 2.024 2.024
## Cadri30a|t3 2.504 0.250 10.011 0.000 2.504 2.504
## Cadri34a|t1 1.328 0.097 13.656 0.000 1.328 1.328
## Cadri34a|t2 2.249 0.192 11.707 0.000 2.249 2.249
## Cadri34a|t3 2.740 0.329 8.326 0.000 2.740 2.740
## Cadri5a|t1 1.717 0.123 13.919 0.000 1.717 1.717
## Cadri5a|t2 2.504 0.250 10.011 0.000 2.504 2.504
## Cadri5a|t3 2.740 0.329 8.326 0.000 2.740 2.740
## Cadri29a|t1 1.292 0.095 13.534 0.000 1.292 1.292
## Cadri29a|t2 2.024 0.157 12.925 0.000 2.024 2.024
## Cadri31a|t1 2.161 0.177 12.220 0.000 2.161 2.161
## Cadri31a|t2 2.504 0.250 10.011 0.000 2.504 2.504
## Cadri31a|t3 2.740 0.329 8.326 0.000 2.740 2.740
## Cadri33a|t1 1.871 0.138 13.536 0.000 1.871 1.871
## Cadri33a|t2 2.357 0.214 11.014 0.000 2.357 2.357
## Cadri33a|t3 2.740 0.329 8.326 0.000 2.740 2.740
## Cadri3a|t1 1.472 0.105 13.974 0.000 1.472 1.472
## Cadri3a|t2 2.161 0.177 12.220 0.000 2.161 2.161
## Cadri3a|t3 2.357 0.214 11.014 0.000 2.357 2.357
## Cadri20a|t1 1.717 0.123 13.919 0.000 1.717 1.717
## Cadri20a|t2 2.161 0.177 12.220 0.000 2.161 2.161
## Cadri20a|t3 2.504 0.250 10.011 0.000 2.504 2.504
## Cadri35a|t1 1.347 0.098 13.713 0.000 1.347 1.347
## Cadri35a|t2 2.161 0.177 12.220 0.000 2.161 2.161
## Cadri35a|t3 2.504 0.250 10.011 0.000 2.504 2.504
## Cadri2a|t1 1.386 0.100 13.817 0.000 1.386 1.386
## Cadri2a|t2 1.968 0.149 13.174 0.000 1.968 1.968
## Cadri2a|t3 2.249 0.192 11.707 0.000 2.249 2.249
## Cadri13a|t1 2.024 0.157 12.925 0.000 2.024 2.024
## Cadri13a|t2 2.740 0.329 8.326 0.000 2.740 2.740
## Cadri15a|t1 2.357 0.214 11.014 0.000 2.357 2.357
## Cadri15a|t2 2.740 0.329 8.326 0.000 2.740 2.740
## Cadri19a|t1 0.558 0.074 7.573 0.000 0.558 0.558
## Cadri19a|t2 1.257 0.094 13.400 0.000 1.257 1.257
## Cadri19a|t3 1.789 0.130 13.772 0.000 1.789 1.789
## Cadri1a|t1 -0.729 0.077 -9.489 0.000 -0.729 -0.729
## Cadri1a|t2 0.321 0.071 4.520 0.000 0.321 0.321
## Cadri1a|t3 0.833 0.079 10.522 0.000 0.833 0.833
## Cadri6a|t1 -0.632 0.075 -8.431 0.000 -0.632 -0.632
## Cadri6a|t2 0.514 0.073 7.032 0.000 0.514 0.514
## Cadri6a|t3 1.310 0.096 13.596 0.000 1.310 1.310
## Cadri10a|t1 -0.889 0.081 -11.024 0.000 -0.889 -0.889
## Cadri10a|t2 0.313 0.071 4.410 0.000 0.313 0.313
## Cadri10a|t3 0.996 0.084 11.895 0.000 0.996 0.996
## Cadri11a|t1 -0.935 0.082 -11.418 0.000 -0.935 -0.935
## Cadri11a|t2 0.403 0.072 5.616 0.000 0.403 0.403
## Cadri11a|t3 1.117 0.088 12.701 0.000 1.117 1.117
## Cadri14a|t1 -0.935 0.082 -11.418 0.000 -0.935 -0.935
## Cadri14a|t2 0.108 0.070 1.546 0.122 0.108 0.108
## Cadri14a|t3 0.759 0.077 9.802 0.000 0.759 0.759
## Cadri16a|t1 -0.549 0.074 -7.465 0.000 -0.549 -0.549
## Cadri16a|t2 0.462 0.072 6.380 0.000 0.462 0.462
## Cadri16a|t3 1.062 0.086 12.353 0.000 1.062 1.062
## Cadri18a|t1 -1.035 0.085 -12.173 0.000 -1.035 -1.035
## Cadri18a|t2 -0.062 0.070 -0.883 0.377 -0.062 -0.062
## Cadri18a|t3 0.595 0.074 8.003 0.000 0.595 0.595
## Cadri22a|t1 -0.749 0.077 -9.698 0.000 -0.749 -0.749
## Cadri22a|t2 0.178 0.070 2.539 0.011 0.178 0.178
## Cadri22a|t3 0.822 0.079 10.420 0.000 0.822 0.822
## Cadri26a|t1 -0.699 0.076 -9.174 0.000 -0.699 -0.699
## Cadri26a|t2 0.420 0.072 5.834 0.000 0.420 0.420
## Cadri26a|t3 1.009 0.084 11.989 0.000 1.009 1.009
## Cadri27a|t1 -0.241 0.070 -3.420 0.001 -0.241 -0.241
## Cadri27a|t2 0.699 0.076 9.174 0.000 0.699 0.699
## Cadri27a|t3 1.367 0.099 13.767 0.000 1.367 1.367
##
## Variances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .Cadri4a 0.637 0.637 0.637
## .Cadri7a 0.398 0.398 0.398
## .Cadri9a 0.543 0.543 0.543
## .Cadri12a 0.489 0.489 0.489
## .Cadri17a 0.379 0.379 0.379
## .Cadri21a 0.633 0.633 0.633
## .Cadri23a 0.726 0.726 0.726
## .Cadri24a 0.503 0.503 0.503
## .Cadri28a 0.452 0.452 0.452
## .Cadri32a 0.538 0.538 0.538
## .Cadri8a 0.295 0.295 0.295
## .Cadri25a 0.322 0.322 0.322
## .Cadri30a 0.275 0.275 0.275
## .Cadri34a 0.334 0.334 0.334
## .Cadri5a 0.702 0.702 0.702
## .Cadri29a 0.626 0.626 0.626
## .Cadri31a 0.529 0.529 0.529
## .Cadri33a 0.247 0.247 0.247
## .Cadri3a 0.627 0.627 0.627
## .Cadri20a 0.348 0.348 0.348
## .Cadri35a 0.520 0.520 0.520
## .Cadri2a 0.604 0.604 0.604
## .Cadri13a 0.775 0.775 0.775
## .Cadri15a -0.388 -0.388 -0.388
## .Cadri19a 0.429 0.429 0.429
## .Cadri1a 0.504 0.504 0.504
## .Cadri6a 0.461 0.461 0.461
## .Cadri10a 0.429 0.429 0.429
## .Cadri11a 0.483 0.483 0.483
## .Cadri14a 0.362 0.362 0.362
## .Cadri16a 0.326 0.326 0.326
## .Cadri18a 0.415 0.415 0.415
## .Cadri22a 0.434 0.434 0.434
## .Cadri26a 0.394 0.394 0.394
## .Cadri27a 0.651 0.651 0.651
## V_verbal 0.363 0.057 6.336 0.000 1.000 1.000
## V_fisica 0.705 0.078 9.050 0.000 1.000 1.000
## C_amenaz 0.298 0.083 3.576 0.000 1.000 1.000
## V_relaci 0.373 0.101 3.679 0.000 1.000 1.000
## V_sexual 0.396 0.116 3.404 0.001 1.000 1.000
## R_confli 0.496 0.048 10.287 0.000 1.000 1.000
##
## Scales y*:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## Cadri4a 1.000 1.000 1.000
## Cadri7a 1.000 1.000 1.000
## Cadri9a 1.000 1.000 1.000
## Cadri12a 1.000 1.000 1.000
## Cadri17a 1.000 1.000 1.000
## Cadri21a 1.000 1.000 1.000
## Cadri23a 1.000 1.000 1.000
## Cadri24a 1.000 1.000 1.000
## Cadri28a 1.000 1.000 1.000
## Cadri32a 1.000 1.000 1.000
## Cadri8a 1.000 1.000 1.000
## Cadri25a 1.000 1.000 1.000
## Cadri30a 1.000 1.000 1.000
## Cadri34a 1.000 1.000 1.000
## Cadri5a 1.000 1.000 1.000
## Cadri29a 1.000 1.000 1.000
## Cadri31a 1.000 1.000 1.000
## Cadri33a 1.000 1.000 1.000
## Cadri3a 1.000 1.000 1.000
## Cadri20a 1.000 1.000 1.000
## Cadri35a 1.000 1.000 1.000
## Cadri2a 1.000 1.000 1.000
## Cadri13a 1.000 1.000 1.000
## Cadri15a 1.000 1.000 1.000
## Cadri19a 1.000 1.000 1.000
## Cadri1a 1.000 1.000 1.000
## Cadri6a 1.000 1.000 1.000
## Cadri10a 1.000 1.000 1.000
## Cadri11a 1.000 1.000 1.000
## Cadri14a 1.000 1.000 1.000
## Cadri16a 1.000 1.000 1.000
## Cadri18a 1.000 1.000 1.000
## Cadri22a 1.000 1.000 1.000
## Cadri26a 1.000 1.000 1.000
## Cadri27a 1.000 1.000 1.000
fit_b)## Warning in lav_start_check_cov(lavpartable = lavpartable, start = START): lavaan WARNING: starting values imply a correlation larger than 1;
## variables involved are: V_fisica C_amenaz
## lhs op rhs mi epc sepc.lv sepc.all sepc.nox
## 11 V_fisica =~ Cadri8a 1240.709 73.231 61.474 61.474 61.474
## 203 Cadri8a ~*~ Cadri8a 1240.709 73.231 73.231 1.000 1.000
## 1031 Cadri16a ~~ Cadri26a 125.369 0.355 0.355 0.989 0.989
## 726 Cadri32a ~~ Cadri13a 109.136 -0.383 -0.383 -0.594 -0.594
## 207 Cadri5a ~*~ Cadri5a 89.095 14.051 14.051 1.000 1.000
## 15 C_amenaz =~ Cadri5a 89.095 14.051 7.673 7.673 7.673
## 322 V_fisica =~ Cadri22a 83.995 0.386 0.324 0.324 0.324
## 291 V_verbal =~ Cadri22a 77.000 0.523 0.315 0.315 0.315
## 353 C_amenaz =~ Cadri22a 73.169 0.515 0.281 0.281 0.281
## 375 V_relaci =~ Cadri13a 69.786 -1.198 -0.731 -0.731 -0.731
## 292 V_verbal =~ Cadri26a 62.109 -0.546 -0.329 -0.329 -0.329
## 281 V_verbal =~ Cadri13a 61.029 -0.834 -0.502 -0.502 -0.502
## 385 V_relaci =~ Cadri22a 58.092 0.457 0.279 0.279 0.279
## 386 V_relaci =~ Cadri26a 57.340 -0.522 -0.318 -0.318 -0.318
## 343 C_amenaz =~ Cadri13a 57.232 -1.231 -0.672 -0.672 -0.672
## 354 C_amenaz =~ Cadri26a 53.545 -0.509 -0.278 -0.278 -0.278
## 323 V_fisica =~ Cadri26a 51.371 -0.354 -0.297 -0.297 -0.297
## 321 V_fisica =~ Cadri18a 50.640 -0.364 -0.306 -0.306 -0.306
## 352 C_amenaz =~ Cadri18a 49.577 -0.503 -0.274 -0.274 -0.274
## 290 V_verbal =~ Cadri18a 46.802 -0.482 -0.290 -0.290 -0.290
## Graficar
semPlot::semPaths(fit01_b, whatLabels = "std", label.cex= 1.2,
edge.label.cex = 0.5, nCharEdges = 3,
nCharNodes = 8, sizeLat = 6, sizeLat2 = 4,
sizeMan = 6, sizeMan2 = 1.5, rotation = 2, intercepts = F,
thresholds = F, groups = "latents", pastel = TRUE,
exoVar = FALSE, edge.color = "black",
curvature = 2, mar = c(1, 12, 2, 12), residScale = 10,
manifests = rev(fit01_b@Data@ordered))## Registered S3 methods overwritten by 'huge':
## method from
## plot.sim BDgraph
## print.sim BDgraph
A partir del análisis descriptivo y la observación del modelo 01, se hacen los siguientes cambios:
model02 <- "# Modelo de medición
V_verbal =~ Cadri4a + Cadri7a + Cadri9a + Cadri12a + Cadri17a + Cadri21a + Cadri23a +
Cadri24a + Cadri28a + Cadri32a
V_fisica =~ Cadri8a + Cadri25a + Cadri30a + Cadri34a
C_amenaz =~ Cadri29a + Cadri31a + Cadri33a
V_relaci =~ Cadri3a + Cadri20a + Cadri35a
V_sexual =~ Cadri2a + Cadri19a
R_confli =~ Cadri1a + Cadri6a + Cadri10a + Cadri11a + Cadri14a + Cadri16a + Cadri18a +
Cadri22a + Cadri26a + Cadri27a"## Warning in lav_object_post_check(object): lavaan WARNING: covariance matrix of latent variables
## is not positive definite;
## use lavInspect(fit, "cov.lv") to investigate.
## lavaan 0.6-6 ended normally after 262 iterations
##
## Estimator ML
## Optimization method NLMINB
## Number of free parameters 79
##
## Number of observations 326
##
## Model Test User Model:
## Standard Robust
## Test Statistic 1349.081 1060.264
## Degrees of freedom 449 449
## P-value (Chi-square) 0.000 0.000
## Scaling correction factor 1.272
## Yuan-Bentler correction (Mplus variant)
##
## Model Test Baseline Model:
##
## Test statistic 4244.153 2989.537
## Degrees of freedom 496 496
## P-value 0.000 0.000
## Scaling correction factor 1.420
##
## User Model versus Baseline Model:
##
## Comparative Fit Index (CFI) 0.760 0.755
## Tucker-Lewis Index (TLI) 0.735 0.729
##
## Robust Comparative Fit Index (CFI) 0.780
## Robust Tucker-Lewis Index (TLI) 0.757
##
## Loglikelihood and Information Criteria:
##
## Loglikelihood user model (H0) -8086.670 -8086.670
## Scaling correction factor 4.767
## for the MLR correction
## Loglikelihood unrestricted model (H1) -7412.129 -7412.129
## Scaling correction factor 1.795
## for the MLR correction
##
## Akaike (AIC) 16331.340 16331.340
## Bayesian (BIC) 16630.505 16630.505
## Sample-size adjusted Bayesian (BIC) 16379.922 16379.922
##
## Root Mean Square Error of Approximation:
##
## RMSEA 0.078 0.065
## 90 Percent confidence interval - lower 0.074 0.060
## 90 Percent confidence interval - upper 0.083 0.069
## P-value RMSEA <= 0.05 0.000 0.000
##
## Robust RMSEA 0.073
## 90 Percent confidence interval - lower 0.067
## 90 Percent confidence interval - upper 0.079
##
## Standardized Root Mean Square Residual:
##
## SRMR 0.082 0.082
##
## Parameter Estimates:
##
## Standard errors Sandwich
## Information bread Observed
## Observed information based on Hessian
##
## Latent Variables:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## V_verbal =~
## Cadri4a 1.000 0.371 0.452
## Cadri7a 1.503 0.250 6.012 0.000 0.558 0.723
## Cadri9a 1.137 0.174 6.517 0.000 0.422 0.549
## Cadri12a 1.229 0.257 4.775 0.000 0.456 0.648
## Cadri17a 1.067 0.213 5.008 0.000 0.396 0.693
## Cadri21a 0.621 0.188 3.292 0.001 0.230 0.474
## Cadri23a 0.371 0.094 3.959 0.000 0.138 0.327
## Cadri24a 0.932 0.196 4.751 0.000 0.346 0.601
## Cadri28a 1.346 0.228 5.913 0.000 0.500 0.633
## Cadri32a 1.251 0.233 5.360 0.000 0.464 0.669
## V_fisica =~
## Cadri8a 1.000 0.261 0.700
## Cadri25a 0.764 0.236 3.234 0.001 0.199 0.558
## Cadri30a 1.194 0.278 4.291 0.000 0.311 0.730
## Cadri34a 0.881 0.218 4.045 0.000 0.230 0.631
## C_amenaz =~
## Cadri29a 1.000 0.112 0.291
## Cadri31a 0.766 0.731 1.047 0.295 0.086 0.390
## Cadri33a 1.325 1.173 1.130 0.259 0.149 0.555
## V_relaci =~
## Cadri3a 1.000 0.127 0.323
## Cadri20a 1.489 1.020 1.461 0.144 0.188 0.554
## Cadri35a 1.601 1.273 1.258 0.209 0.203 0.517
## V_sexual =~
## Cadri2a 1.000 0.211 0.467
## Cadri19a 2.021 1.535 1.317 0.188 0.426 0.549
## R_confli =~
## Cadri1a 1.000 0.663 0.633
## Cadri6a 0.888 0.074 12.055 0.000 0.589 0.644
## Cadri10a 0.965 0.089 10.888 0.000 0.640 0.667
## Cadri11a 0.909 0.075 12.051 0.000 0.603 0.664
## Cadri14a 1.171 0.098 11.899 0.000 0.776 0.758
## Cadri16a 1.097 0.101 10.816 0.000 0.727 0.722
## Cadri18a 1.153 0.101 11.358 0.000 0.764 0.735
## Cadri22a 1.012 0.107 9.435 0.000 0.671 0.637
## Cadri26a 1.033 0.100 10.343 0.000 0.685 0.690
## Cadri27a 0.735 0.090 8.142 0.000 0.487 0.514
##
## Covariances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## V_verbal ~~
## V_fisica 0.059 0.021 2.829 0.005 0.611 0.611
## C_amenaz 0.030 0.021 1.416 0.157 0.724 0.724
## V_relaci 0.037 0.024 1.509 0.131 0.784 0.784
## V_sexual 0.035 0.017 2.058 0.040 0.441 0.441
## R_confli 0.099 0.024 4.188 0.000 0.401 0.401
## V_fisica ~~
## C_amenaz 0.031 0.018 1.733 0.083 1.052 1.052
## V_relaci 0.010 0.013 0.792 0.428 0.307 0.307
## V_sexual 0.027 0.011 2.362 0.018 0.491 0.491
## R_confli 0.025 0.010 2.476 0.013 0.146 0.146
## C_amenaz ~~
## V_relaci 0.011 0.014 0.776 0.438 0.781 0.781
## V_sexual 0.013 0.016 0.791 0.429 0.538 0.538
## R_confli 0.014 0.018 0.783 0.433 0.190 0.190
## V_relaci ~~
## V_sexual 0.015 0.019 0.781 0.435 0.549 0.549
## R_confli 0.017 0.012 1.353 0.176 0.201 0.201
## V_sexual ~~
## R_confli 0.045 0.024 1.890 0.059 0.326 0.326
##
## Variances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .Cadri4a 0.536 0.057 9.413 0.000 0.536 0.795
## .Cadri7a 0.284 0.032 8.765 0.000 0.284 0.477
## .Cadri9a 0.413 0.049 8.512 0.000 0.413 0.699
## .Cadri12a 0.287 0.042 6.793 0.000 0.287 0.580
## .Cadri17a 0.169 0.023 7.350 0.000 0.169 0.519
## .Cadri21a 0.183 0.034 5.389 0.000 0.183 0.775
## .Cadri23a 0.159 0.041 3.909 0.000 0.159 0.893
## .Cadri24a 0.211 0.023 9.083 0.000 0.211 0.638
## .Cadri28a 0.374 0.042 8.955 0.000 0.374 0.600
## .Cadri32a 0.266 0.037 7.112 0.000 0.266 0.552
## .Cadri8a 0.071 0.015 4.739 0.000 0.071 0.510
## .Cadri25a 0.088 0.020 4.290 0.000 0.088 0.689
## .Cadri30a 0.085 0.030 2.881 0.004 0.085 0.468
## .Cadri34a 0.080 0.023 3.468 0.001 0.080 0.602
## .Cadri29a 0.136 0.026 5.263 0.000 0.136 0.915
## .Cadri31a 0.041 0.024 1.683 0.092 0.041 0.848
## .Cadri33a 0.050 0.025 1.974 0.048 0.050 0.692
## .Cadri3a 0.138 0.043 3.172 0.002 0.138 0.896
## .Cadri20a 0.080 0.032 2.494 0.013 0.080 0.693
## .Cadri35a 0.112 0.031 3.636 0.000 0.112 0.733
## .Cadri2a 0.159 0.040 3.950 0.000 0.159 0.782
## .Cadri19a 0.420 0.150 2.801 0.005 0.420 0.698
## .Cadri1a 0.657 0.058 11.294 0.000 0.657 0.599
## .Cadri6a 0.488 0.048 10.080 0.000 0.488 0.585
## .Cadri10a 0.511 0.051 9.935 0.000 0.511 0.555
## .Cadri11a 0.460 0.048 9.562 0.000 0.460 0.559
## .Cadri14a 0.445 0.050 8.836 0.000 0.445 0.425
## .Cadri16a 0.487 0.055 8.854 0.000 0.487 0.479
## .Cadri18a 0.497 0.053 9.392 0.000 0.497 0.460
## .Cadri22a 0.657 0.068 9.715 0.000 0.657 0.594
## .Cadri26a 0.517 0.056 9.215 0.000 0.517 0.524
## .Cadri27a 0.662 0.053 12.476 0.000 0.662 0.736
## V_verbal 0.138 0.041 3.360 0.001 1.000 1.000
## V_fisica 0.068 0.032 2.142 0.032 1.000 1.000
## C_amenaz 0.013 0.011 1.096 0.273 1.000 1.000
## V_relaci 0.016 0.019 0.858 0.391 1.000 1.000
## V_sexual 0.044 0.037 1.207 0.228 1.000 1.000
## R_confli 0.439 0.065 6.797 0.000 1.000 1.000
## Warning in lav_start_check_cov(lavpartable = lavpartable, start = START): lavaan WARNING: starting values imply a correlation larger than 1;
## variables involved are: V_fisica C_amenaz
## lhs op rhs mi epc sepc.lv sepc.all sepc.nox
## 734 Cadri16a ~~ Cadri26a 81.228 0.291 0.291 0.579 0.579
## 556 Cadri30a ~~ Cadri3a 63.069 0.055 0.055 0.512 0.512
## 607 Cadri31a ~~ Cadri3a 47.289 0.030 0.030 0.401 0.401
## 554 Cadri30a ~~ Cadri31a 39.221 0.025 0.025 0.417 0.417
## 181 V_relaci =~ Cadri33a 28.708 -1.290 -0.163 -0.609 -0.609
## 133 V_fisica =~ Cadri22a 28.057 1.074 0.280 0.266 0.266
## 516 Cadri8a ~~ Cadri33a 27.128 0.021 0.021 0.360 0.360
## 171 V_relaci =~ Cadri23a 25.983 2.131 0.270 0.639 0.639
## 684 Cadri2a ~~ Cadri22a 23.960 -0.097 -0.097 -0.302 -0.302
## 105 V_verbal =~ Cadri22a 23.361 0.726 0.270 0.256 0.256
## 590 Cadri29a ~~ Cadri33a 22.536 -0.026 -0.026 -0.318 -0.318
## 170 V_relaci =~ Cadri21a 22.525 2.161 0.273 0.563 0.563
## 90 V_verbal =~ Cadri29a 21.789 0.443 0.165 0.428 0.428
## 162 C_amenaz =~ Cadri22a 21.635 2.179 0.244 0.232 0.232
## 722 Cadri11a ~~ Cadri16a 19.652 -0.133 -0.133 -0.282 -0.282
## 403 Cadri21a ~~ Cadri20a 19.338 0.032 0.032 0.266 0.266
## 200 V_sexual =~ Cadri23a 18.932 0.807 0.170 0.403 0.403
## 404 Cadri21a ~~ Cadri35a 18.846 0.037 0.037 0.260 0.260
## 429 Cadri23a ~~ Cadri35a 18.352 0.034 0.034 0.253 0.253
## 104 V_verbal =~ Cadri18a 18.335 -0.578 -0.215 -0.207 -0.207
fit02_b <- cfa(model = model02,
data = cadri_data,
ordered = TRUE,
estimator = "WLSMV",
mimic = "Mplus")## Warning in lav_model_vcov(lavmodel = lavmodel, lavsamplestats = lavsamplestats, : lavaan WARNING:
## The variance-covariance matrix of the estimated parameters (vcov)
## does not appear to be positive definite! The smallest eigenvalue
## (= -5.562418e-17) is smaller than zero. This may be a symptom that
## the model is not identified.
## Warning in lav_object_post_check(object): lavaan WARNING: covariance matrix of latent variables
## is not positive definite;
## use lavInspect(fit, "cov.lv") to investigate.
## lavaan 0.6-6 ended normally after 67 iterations
##
## Estimator DWLS
## Optimization method NLMINB
## Number of free parameters 141
##
## Number of observations 326
##
## Model Test User Model:
## Standard Robust
## Test Statistic 1036.245 843.596
## Degrees of freedom 449 449
## P-value (Chi-square) 0.000 0.000
## Scaling correction factor 1.823
## Shift parameter 275.200
## simple second-order correction (WLSMV)
##
## Model Test Baseline Model:
##
## Test statistic 18715.935 6266.895
## Degrees of freedom 496 496
## P-value 0.000 0.000
## Scaling correction factor 3.157
##
## User Model versus Baseline Model:
##
## Comparative Fit Index (CFI) 0.968 0.932
## Tucker-Lewis Index (TLI) 0.964 0.924
##
## Robust Comparative Fit Index (CFI) NA
## Robust Tucker-Lewis Index (TLI) NA
##
## Root Mean Square Error of Approximation:
##
## RMSEA 0.063 0.052
## 90 Percent confidence interval - lower 0.058 0.047
## 90 Percent confidence interval - upper 0.069 0.057
## P-value RMSEA <= 0.05 0.000 0.266
##
## Robust RMSEA NA
## 90 Percent confidence interval - lower NA
## 90 Percent confidence interval - upper NA
##
## Standardized Root Mean Square Residual:
##
## SRMR 0.119 0.119
##
## Weighted Root Mean Square Residual:
##
## WRMR 1.325 1.325
##
## Parameter Estimates:
##
## Standard errors Robust.sem
## Information Expected
## Information saturated (h1) model Unstructured
##
## Latent Variables:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## V_verbal =~
## Cadri4a 1.000 0.603 0.603
## Cadri7a 1.288 0.106 12.157 0.000 0.776 0.776
## Cadri9a 1.123 0.103 10.928 0.000 0.677 0.677
## Cadri12a 1.178 0.111 10.625 0.000 0.710 0.710
## Cadri17a 1.305 0.115 11.335 0.000 0.787 0.787
## Cadri21a 0.998 0.123 8.083 0.000 0.602 0.602
## Cadri23a 0.859 0.121 7.077 0.000 0.518 0.518
## Cadri24a 1.164 0.094 12.325 0.000 0.702 0.702
## Cadri28a 1.203 0.107 11.294 0.000 0.725 0.725
## Cadri32a 1.178 0.103 11.468 0.000 0.710 0.710
## V_fisica =~
## Cadri8a 1.000 0.832 0.832
## Cadri25a 0.945 0.080 11.816 0.000 0.787 0.787
## Cadri30a 1.069 0.091 11.716 0.000 0.889 0.889
## Cadri34a 0.985 0.082 12.063 0.000 0.819 0.819
## C_amenaz =~
## Cadri29a 1.000 0.608 0.608
## Cadri31a 1.141 0.185 6.174 0.000 0.694 0.694
## Cadri33a 1.428 0.192 7.425 0.000 0.869 0.869
## V_relaci =~
## Cadri3a 1.000 0.620 0.620
## Cadri20a 1.291 0.217 5.939 0.000 0.800 0.800
## Cadri35a 1.117 0.181 6.163 0.000 0.692 0.692
## V_sexual =~
## Cadri2a 1.000 0.596 0.596
## Cadri19a 1.330 0.289 4.605 0.000 0.793 0.793
## R_confli =~
## Cadri1a 1.000 0.702 0.702
## Cadri6a 1.045 0.056 18.606 0.000 0.733 0.733
## Cadri10a 1.075 0.061 17.532 0.000 0.754 0.754
## Cadri11a 1.027 0.059 17.295 0.000 0.721 0.721
## Cadri14a 1.141 0.062 18.269 0.000 0.800 0.800
## Cadri16a 1.170 0.058 20.166 0.000 0.821 0.821
## Cadri18a 1.092 0.063 17.295 0.000 0.766 0.766
## Cadri22a 1.072 0.064 16.684 0.000 0.752 0.752
## Cadri26a 1.108 0.056 19.879 0.000 0.778 0.778
## Cadri27a 0.841 0.063 13.294 0.000 0.590 0.590
##
## Covariances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## V_verbal ~~
## V_fisica 0.371 0.045 8.266 0.000 0.740 0.740
## C_amenaz 0.328 0.043 7.694 0.000 0.895 0.895
## V_relaci 0.321 0.057 5.599 0.000 0.859 0.859
## V_sexual 0.168 0.045 3.782 0.000 0.469 0.469
## R_confli 0.219 0.029 7.424 0.000 0.518 0.518
## V_fisica ~~
## C_amenaz 0.509 0.065 7.824 0.000 1.004 1.004
## V_relaci 0.255 0.074 3.442 0.001 0.495 0.495
## V_sexual 0.267 0.063 4.238 0.000 0.538 0.538
## R_confli 0.150 0.040 3.759 0.000 0.258 0.258
## C_amenaz ~~
## V_relaci 0.303 0.058 5.229 0.000 0.804 0.804
## V_sexual 0.275 0.069 4.001 0.000 0.759 0.759
## R_confli 0.176 0.036 4.912 0.000 0.411 0.411
## V_relaci ~~
## V_sexual 0.223 0.060 3.722 0.000 0.605 0.605
## R_confli 0.134 0.042 3.159 0.002 0.307 0.307
## V_sexual ~~
## R_confli 0.146 0.043 3.418 0.001 0.350 0.350
##
## Intercepts:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .Cadri4a 0.000 0.000 0.000
## .Cadri7a 0.000 0.000 0.000
## .Cadri9a 0.000 0.000 0.000
## .Cadri12a 0.000 0.000 0.000
## .Cadri17a 0.000 0.000 0.000
## .Cadri21a 0.000 0.000 0.000
## .Cadri23a 0.000 0.000 0.000
## .Cadri24a 0.000 0.000 0.000
## .Cadri28a 0.000 0.000 0.000
## .Cadri32a 0.000 0.000 0.000
## .Cadri8a 0.000 0.000 0.000
## .Cadri25a 0.000 0.000 0.000
## .Cadri30a 0.000 0.000 0.000
## .Cadri34a 0.000 0.000 0.000
## .Cadri29a 0.000 0.000 0.000
## .Cadri31a 0.000 0.000 0.000
## .Cadri33a 0.000 0.000 0.000
## .Cadri3a 0.000 0.000 0.000
## .Cadri20a 0.000 0.000 0.000
## .Cadri35a 0.000 0.000 0.000
## .Cadri2a 0.000 0.000 0.000
## .Cadri19a 0.000 0.000 0.000
## .Cadri1a 0.000 0.000 0.000
## .Cadri6a 0.000 0.000 0.000
## .Cadri10a 0.000 0.000 0.000
## .Cadri11a 0.000 0.000 0.000
## .Cadri14a 0.000 0.000 0.000
## .Cadri16a 0.000 0.000 0.000
## .Cadri18a 0.000 0.000 0.000
## .Cadri22a 0.000 0.000 0.000
## .Cadri26a 0.000 0.000 0.000
## .Cadri27a 0.000 0.000 0.000
## V_verbal 0.000 0.000 0.000
## V_fisica 0.000 0.000 0.000
## C_amenaz 0.000 0.000 0.000
## V_relaci 0.000 0.000 0.000
## V_sexual 0.000 0.000 0.000
## R_confli 0.000 0.000 0.000
##
## Thresholds:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## Cadri4a|t1 -0.069 0.070 -0.994 0.320 -0.069 -0.069
## Cadri4a|t2 1.035 0.085 12.173 0.000 1.035 1.035
## Cadri4a|t3 1.717 0.123 13.919 0.000 1.717 1.717
## Cadri7a|t1 0.178 0.070 2.539 0.011 0.178 0.178
## Cadri7a|t2 1.347 0.098 13.713 0.000 1.347 1.347
## Cadri7a|t3 1.717 0.123 13.919 0.000 1.717 1.717
## Cadri9a|t1 0.015 0.070 0.221 0.825 0.015 0.015
## Cadri9a|t2 1.177 0.090 13.029 0.000 1.177 1.177
## Cadri9a|t3 1.871 0.138 13.536 0.000 1.871 1.871
## Cadri12a|t1 0.549 0.074 7.465 0.000 0.549 0.549
## Cadri12a|t2 1.495 0.107 14.000 0.000 1.495 1.495
## Cadri12a|t3 1.871 0.138 13.536 0.000 1.871 1.871
## Cadri17a|t1 0.844 0.079 10.623 0.000 0.844 0.844
## Cadri17a|t2 1.654 0.118 14.003 0.000 1.654 1.654
## Cadri17a|t3 2.357 0.214 11.014 0.000 2.357 2.357
## Cadri21a|t1 1.089 0.087 12.530 0.000 1.089 1.089
## Cadri21a|t2 1.917 0.143 13.374 0.000 1.917 1.917
## Cadri21a|t3 2.357 0.214 11.014 0.000 2.357 2.357
## Cadri23a|t1 1.224 0.092 13.258 0.000 1.224 1.224
## Cadri23a|t2 2.088 0.166 12.614 0.000 2.088 2.088
## Cadri23a|t3 2.504 0.250 10.011 0.000 2.504 2.504
## Cadri24a|t1 0.445 0.072 6.162 0.000 0.445 0.445
## Cadri24a|t2 1.871 0.138 13.536 0.000 1.871 1.871
## Cadri24a|t3 2.357 0.214 11.014 0.000 2.357 2.357
## Cadri28a|t1 0.462 0.072 6.380 0.000 0.462 0.462
## Cadri28a|t2 1.177 0.090 13.029 0.000 1.177 1.177
## Cadri28a|t3 1.828 0.134 13.667 0.000 1.828 1.828
## Cadri32a|t1 0.622 0.075 8.324 0.000 0.622 0.622
## Cadri32a|t2 1.569 0.112 14.040 0.000 1.569 1.569
## Cadri32a|t3 1.828 0.134 13.667 0.000 1.828 1.828
## Cadri8a|t1 1.347 0.098 13.713 0.000 1.347 1.347
## Cadri8a|t2 2.161 0.177 12.220 0.000 2.161 2.161
## Cadri8a|t3 2.740 0.329 8.326 0.000 2.740 2.740
## Cadri25a|t1 1.257 0.094 13.400 0.000 1.257 1.257
## Cadri25a|t2 2.249 0.192 11.707 0.000 2.249 2.249
## Cadri30a|t1 1.257 0.094 13.400 0.000 1.257 1.257
## Cadri30a|t2 2.024 0.157 12.925 0.000 2.024 2.024
## Cadri30a|t3 2.504 0.250 10.011 0.000 2.504 2.504
## Cadri34a|t1 1.328 0.097 13.656 0.000 1.328 1.328
## Cadri34a|t2 2.249 0.192 11.707 0.000 2.249 2.249
## Cadri34a|t3 2.740 0.329 8.326 0.000 2.740 2.740
## Cadri29a|t1 1.292 0.095 13.534 0.000 1.292 1.292
## Cadri29a|t2 2.024 0.157 12.925 0.000 2.024 2.024
## Cadri31a|t1 2.161 0.177 12.220 0.000 2.161 2.161
## Cadri31a|t2 2.504 0.250 10.011 0.000 2.504 2.504
## Cadri31a|t3 2.740 0.329 8.326 0.000 2.740 2.740
## Cadri33a|t1 1.871 0.138 13.536 0.000 1.871 1.871
## Cadri33a|t2 2.357 0.214 11.014 0.000 2.357 2.357
## Cadri33a|t3 2.740 0.329 8.326 0.000 2.740 2.740
## Cadri3a|t1 1.472 0.105 13.974 0.000 1.472 1.472
## Cadri3a|t2 2.161 0.177 12.220 0.000 2.161 2.161
## Cadri3a|t3 2.357 0.214 11.014 0.000 2.357 2.357
## Cadri20a|t1 1.717 0.123 13.919 0.000 1.717 1.717
## Cadri20a|t2 2.161 0.177 12.220 0.000 2.161 2.161
## Cadri20a|t3 2.504 0.250 10.011 0.000 2.504 2.504
## Cadri35a|t1 1.347 0.098 13.713 0.000 1.347 1.347
## Cadri35a|t2 2.161 0.177 12.220 0.000 2.161 2.161
## Cadri35a|t3 2.504 0.250 10.011 0.000 2.504 2.504
## Cadri2a|t1 1.386 0.100 13.817 0.000 1.386 1.386
## Cadri2a|t2 1.968 0.149 13.174 0.000 1.968 1.968
## Cadri2a|t3 2.249 0.192 11.707 0.000 2.249 2.249
## Cadri19a|t1 0.558 0.074 7.573 0.000 0.558 0.558
## Cadri19a|t2 1.257 0.094 13.400 0.000 1.257 1.257
## Cadri19a|t3 1.789 0.130 13.772 0.000 1.789 1.789
## Cadri1a|t1 -0.729 0.077 -9.489 0.000 -0.729 -0.729
## Cadri1a|t2 0.321 0.071 4.520 0.000 0.321 0.321
## Cadri1a|t3 0.833 0.079 10.522 0.000 0.833 0.833
## Cadri6a|t1 -0.632 0.075 -8.431 0.000 -0.632 -0.632
## Cadri6a|t2 0.514 0.073 7.032 0.000 0.514 0.514
## Cadri6a|t3 1.310 0.096 13.596 0.000 1.310 1.310
## Cadri10a|t1 -0.889 0.081 -11.024 0.000 -0.889 -0.889
## Cadri10a|t2 0.313 0.071 4.410 0.000 0.313 0.313
## Cadri10a|t3 0.996 0.084 11.895 0.000 0.996 0.996
## Cadri11a|t1 -0.935 0.082 -11.418 0.000 -0.935 -0.935
## Cadri11a|t2 0.403 0.072 5.616 0.000 0.403 0.403
## Cadri11a|t3 1.117 0.088 12.701 0.000 1.117 1.117
## Cadri14a|t1 -0.935 0.082 -11.418 0.000 -0.935 -0.935
## Cadri14a|t2 0.108 0.070 1.546 0.122 0.108 0.108
## Cadri14a|t3 0.759 0.077 9.802 0.000 0.759 0.759
## Cadri16a|t1 -0.549 0.074 -7.465 0.000 -0.549 -0.549
## Cadri16a|t2 0.462 0.072 6.380 0.000 0.462 0.462
## Cadri16a|t3 1.062 0.086 12.353 0.000 1.062 1.062
## Cadri18a|t1 -1.035 0.085 -12.173 0.000 -1.035 -1.035
## Cadri18a|t2 -0.062 0.070 -0.883 0.377 -0.062 -0.062
## Cadri18a|t3 0.595 0.074 8.003 0.000 0.595 0.595
## Cadri22a|t1 -0.749 0.077 -9.698 0.000 -0.749 -0.749
## Cadri22a|t2 0.178 0.070 2.539 0.011 0.178 0.178
## Cadri22a|t3 0.822 0.079 10.420 0.000 0.822 0.822
## Cadri26a|t1 -0.699 0.076 -9.174 0.000 -0.699 -0.699
## Cadri26a|t2 0.420 0.072 5.834 0.000 0.420 0.420
## Cadri26a|t3 1.009 0.084 11.989 0.000 1.009 1.009
## Cadri27a|t1 -0.241 0.070 -3.420 0.001 -0.241 -0.241
## Cadri27a|t2 0.699 0.076 9.174 0.000 0.699 0.699
## Cadri27a|t3 1.367 0.099 13.767 0.000 1.367 1.367
##
## Variances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .Cadri4a 0.636 0.636 0.636
## .Cadri7a 0.397 0.397 0.397
## .Cadri9a 0.542 0.542 0.542
## .Cadri12a 0.495 0.495 0.495
## .Cadri17a 0.381 0.381 0.381
## .Cadri21a 0.638 0.638 0.638
## .Cadri23a 0.732 0.732 0.732
## .Cadri24a 0.507 0.507 0.507
## .Cadri28a 0.474 0.474 0.474
## .Cadri32a 0.496 0.496 0.496
## .Cadri8a 0.308 0.308 0.308
## .Cadri25a 0.381 0.381 0.381
## .Cadri30a 0.209 0.209 0.209
## .Cadri34a 0.329 0.329 0.329
## .Cadri29a 0.630 0.630 0.630
## .Cadri31a 0.518 0.518 0.518
## .Cadri33a 0.245 0.245 0.245
## .Cadri3a 0.616 0.616 0.616
## .Cadri20a 0.360 0.360 0.360
## .Cadri35a 0.521 0.521 0.521
## .Cadri2a 0.645 0.645 0.645
## .Cadri19a 0.372 0.372 0.372
## .Cadri1a 0.508 0.508 0.508
## .Cadri6a 0.462 0.462 0.462
## .Cadri10a 0.431 0.431 0.431
## .Cadri11a 0.481 0.481 0.481
## .Cadri14a 0.360 0.360 0.360
## .Cadri16a 0.326 0.326 0.326
## .Cadri18a 0.413 0.413 0.413
## .Cadri22a 0.434 0.434 0.434
## .Cadri26a 0.395 0.395 0.395
## .Cadri27a 0.652 0.652 0.652
## V_verbal 0.364 0.057 6.343 0.000 1.000 1.000
## V_fisica 0.692 0.076 9.063 0.000 1.000 1.000
## C_amenaz 0.370 0.073 5.062 0.000 1.000 1.000
## V_relaci 0.384 0.102 3.772 0.000 1.000 1.000
## V_sexual 0.355 0.106 3.345 0.001 1.000 1.000
## R_confli 0.492 0.048 10.228 0.000 1.000 1.000
##
## Scales y*:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## Cadri4a 1.000 1.000 1.000
## Cadri7a 1.000 1.000 1.000
## Cadri9a 1.000 1.000 1.000
## Cadri12a 1.000 1.000 1.000
## Cadri17a 1.000 1.000 1.000
## Cadri21a 1.000 1.000 1.000
## Cadri23a 1.000 1.000 1.000
## Cadri24a 1.000 1.000 1.000
## Cadri28a 1.000 1.000 1.000
## Cadri32a 1.000 1.000 1.000
## Cadri8a 1.000 1.000 1.000
## Cadri25a 1.000 1.000 1.000
## Cadri30a 1.000 1.000 1.000
## Cadri34a 1.000 1.000 1.000
## Cadri29a 1.000 1.000 1.000
## Cadri31a 1.000 1.000 1.000
## Cadri33a 1.000 1.000 1.000
## Cadri3a 1.000 1.000 1.000
## Cadri20a 1.000 1.000 1.000
## Cadri35a 1.000 1.000 1.000
## Cadri2a 1.000 1.000 1.000
## Cadri19a 1.000 1.000 1.000
## Cadri1a 1.000 1.000 1.000
## Cadri6a 1.000 1.000 1.000
## Cadri10a 1.000 1.000 1.000
## Cadri11a 1.000 1.000 1.000
## Cadri14a 1.000 1.000 1.000
## Cadri16a 1.000 1.000 1.000
## Cadri18a 1.000 1.000 1.000
## Cadri22a 1.000 1.000 1.000
## Cadri26a 1.000 1.000 1.000
## Cadri27a 1.000 1.000 1.000
## Graficar
semPlot::semPaths(fit02_b, whatLabels = "std", label.cex= 1.2,
edge.label.cex = 0.5, nCharEdges = 3,
nCharNodes = 8, sizeLat = 6, sizeLat2 = 4,
sizeMan = 6, sizeMan2 = 1.5, rotation = 2, intercepts = F,
thresholds = F, groups = "latents", pastel = TRUE,
exoVar = FALSE, edge.color = "black",
curvature = 2, mar = c(1, 12, 2, 12), residScale = 10,
manifests = rev(fit02_b@Data@ordered))
title("Modelo Factorial del CADRI \n Modelo 02")Se mantienen los cambios del Modelo 02: - Sin item 15, 13 (V Sexual) - Sin item 05 (Conducta amenzante)
Se adiciona el siguiente cambio: - No considerar al factor Resolución de conflictos como parte del modelo factorial
model03 <- "# Modelo de medición
V_verbal =~ Cadri4a + Cadri7a + Cadri9a + Cadri12a + Cadri17a + Cadri21a + Cadri23a +
Cadri24a + Cadri28a + Cadri32a
V_fisica =~ Cadri8a + Cadri25a + Cadri30a + Cadri34a
C_amenaz =~ Cadri29a + Cadri31a + Cadri33a
V_relaci =~ Cadri3a + Cadri20a + Cadri35a
V_sexual =~ Cadri2a + Cadri19a"## Warning in lav_object_post_check(object): lavaan WARNING: covariance matrix of latent variables
## is not positive definite;
## use lavInspect(fit, "cov.lv") to investigate.
## lavaan 0.6-6 ended normally after 261 iterations
##
## Estimator ML
## Optimization method NLMINB
## Number of free parameters 54
##
## Number of observations 326
##
## Model Test User Model:
## Standard Robust
## Test Statistic 719.059 456.499
## Degrees of freedom 199 199
## P-value (Chi-square) 0.000 0.000
## Scaling correction factor 1.575
## Yuan-Bentler correction (Mplus variant)
##
## Model Test Baseline Model:
##
## Test statistic 2322.424 1250.743
## Degrees of freedom 231 231
## P-value 0.000 0.000
## Scaling correction factor 1.857
##
## User Model versus Baseline Model:
##
## Comparative Fit Index (CFI) 0.751 0.747
## Tucker-Lewis Index (TLI) 0.711 0.707
##
## Robust Comparative Fit Index (CFI) 0.786
## Robust Tucker-Lewis Index (TLI) 0.751
##
## Loglikelihood and Information Criteria:
##
## Loglikelihood user model (H0) -4146.842 -4146.842
## Scaling correction factor 6.547
## for the MLR correction
## Loglikelihood unrestricted model (H1) -3787.312 -3787.312
## Scaling correction factor 2.636
## for the MLR correction
##
## Akaike (AIC) 8401.684 8401.684
## Bayesian (BIC) 8606.177 8606.177
## Sample-size adjusted Bayesian (BIC) 8434.892 8434.892
##
## Root Mean Square Error of Approximation:
##
## RMSEA 0.090 0.063
## 90 Percent confidence interval - lower 0.083 0.057
## 90 Percent confidence interval - upper 0.097 0.069
## P-value RMSEA <= 0.05 0.000 0.000
##
## Robust RMSEA 0.079
## 90 Percent confidence interval - lower 0.070
## 90 Percent confidence interval - upper 0.089
##
## Standardized Root Mean Square Residual:
##
## SRMR 0.078 0.078
##
## Parameter Estimates:
##
## Standard errors Sandwich
## Information bread Observed
## Observed information based on Hessian
##
## Latent Variables:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## V_verbal =~
## Cadri4a 1.000 0.358 0.436
## Cadri7a 1.545 0.263 5.875 0.000 0.553 0.716
## Cadri9a 1.159 0.184 6.288 0.000 0.415 0.540
## Cadri12a 1.294 0.271 4.772 0.000 0.463 0.658
## Cadri17a 1.120 0.226 4.959 0.000 0.401 0.702
## Cadri21a 0.658 0.197 3.336 0.001 0.235 0.484
## Cadri23a 0.389 0.098 3.981 0.000 0.139 0.330
## Cadri24a 0.950 0.207 4.589 0.000 0.340 0.591
## Cadri28a 1.383 0.240 5.767 0.000 0.495 0.627
## Cadri32a 1.320 0.243 5.427 0.000 0.472 0.681
## V_fisica =~
## Cadri8a 1.000 0.260 0.697
## Cadri25a 0.767 0.236 3.247 0.001 0.199 0.557
## Cadri30a 1.203 0.282 4.264 0.000 0.312 0.732
## Cadri34a 0.888 0.220 4.029 0.000 0.231 0.633
## C_amenaz =~
## Cadri29a 1.000 0.112 0.292
## Cadri31a 0.766 0.720 1.065 0.287 0.086 0.391
## Cadri33a 1.323 1.123 1.177 0.239 0.148 0.554
## V_relaci =~
## Cadri3a 1.000 0.127 0.324
## Cadri20a 1.472 1.017 1.448 0.148 0.187 0.550
## Cadri35a 1.602 1.292 1.240 0.215 0.203 0.519
## V_sexual =~
## Cadri2a 1.000 0.213 0.471
## Cadri19a 1.984 1.826 1.086 0.277 0.422 0.544
##
## Covariances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## V_verbal ~~
## V_fisica 0.057 0.020 2.791 0.005 0.611 0.611
## C_amenaz 0.029 0.020 1.488 0.137 0.724 0.724
## V_relaci 0.036 0.024 1.484 0.138 0.784 0.784
## V_sexual 0.033 0.018 1.878 0.060 0.440 0.440
## V_fisica ~~
## C_amenaz 0.031 0.017 1.803 0.071 1.052 1.052
## V_relaci 0.010 0.013 0.786 0.432 0.309 0.309
## V_sexual 0.027 0.012 2.270 0.023 0.491 0.491
## C_amenaz ~~
## V_relaci 0.011 0.014 0.789 0.430 0.784 0.784
## V_sexual 0.013 0.016 0.796 0.426 0.538 0.538
## V_relaci ~~
## V_sexual 0.015 0.021 0.721 0.471 0.556 0.556
##
## Variances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .Cadri4a 0.546 0.057 9.580 0.000 0.546 0.810
## .Cadri7a 0.290 0.033 8.815 0.000 0.290 0.487
## .Cadri9a 0.419 0.049 8.547 0.000 0.419 0.709
## .Cadri12a 0.281 0.042 6.625 0.000 0.281 0.567
## .Cadri17a 0.166 0.023 7.135 0.000 0.166 0.507
## .Cadri21a 0.181 0.034 5.342 0.000 0.181 0.765
## .Cadri23a 0.159 0.041 3.891 0.000 0.159 0.891
## .Cadri24a 0.215 0.024 9.134 0.000 0.215 0.651
## .Cadri28a 0.379 0.043 8.838 0.000 0.379 0.607
## .Cadri32a 0.258 0.037 6.893 0.000 0.258 0.537
## .Cadri8a 0.071 0.015 4.726 0.000 0.071 0.515
## .Cadri25a 0.088 0.020 4.319 0.000 0.088 0.689
## .Cadri30a 0.085 0.029 2.881 0.004 0.085 0.464
## .Cadri34a 0.079 0.023 3.476 0.001 0.079 0.599
## .Cadri29a 0.136 0.026 5.244 0.000 0.136 0.915
## .Cadri31a 0.041 0.024 1.691 0.091 0.041 0.847
## .Cadri33a 0.050 0.025 1.989 0.047 0.050 0.693
## .Cadri3a 0.137 0.043 3.163 0.002 0.137 0.895
## .Cadri20a 0.081 0.032 2.492 0.013 0.081 0.697
## .Cadri35a 0.112 0.031 3.628 0.000 0.112 0.730
## .Cadri2a 0.158 0.045 3.517 0.000 0.158 0.778
## .Cadri19a 0.423 0.174 2.427 0.015 0.423 0.704
## V_verbal 0.128 0.040 3.210 0.001 1.000 1.000
## V_fisica 0.067 0.032 2.136 0.033 1.000 1.000
## C_amenaz 0.013 0.011 1.153 0.249 1.000 1.000
## V_relaci 0.016 0.019 0.849 0.396 1.000 1.000
## V_sexual 0.045 0.044 1.037 0.300 1.000 1.000
## Warning in lav_start_check_cov(lavpartable = lavpartable, start = START): lavaan WARNING: starting values imply a correlation larger than 1;
## variables involved are: V_fisica C_amenaz
## lhs op rhs mi epc sepc.lv sepc.all sepc.nox
## 108 C_amenaz =~ Cadri19a 104.908 119.548 13.420 17.313 17.313
## 338 Cadri30a ~~ Cadri3a 62.845 0.055 0.055 0.512 0.512
## 359 Cadri31a ~~ Cadri3a 47.139 0.030 0.030 0.401 0.401
## 336 Cadri30a ~~ Cadri31a 39.024 0.025 0.025 0.417 0.417
## 107 C_amenaz =~ Cadri2a 31.334 -13.555 -1.522 -3.373 -3.373
## 125 V_relaci =~ Cadri33a 30.436 -1.328 -0.169 -0.629 -0.629
## 318 Cadri8a ~~ Cadri33a 27.702 0.022 0.022 0.363 0.363
## 115 V_relaci =~ Cadri23a 25.949 2.221 0.282 0.668 0.668
## 112 V_relaci =~ Cadri12a 23.381 -2.980 -0.378 -0.538 -0.538
## 352 Cadri29a ~~ Cadri33a 22.623 -0.026 -0.026 -0.319 -0.319
## 134 V_sexual =~ Cadri23a 21.525 0.866 0.184 0.436 0.436
## 255 Cadri21a ~~ Cadri20a 20.346 0.033 0.033 0.273 0.273
## 256 Cadri21a ~~ Cadri35a 20.262 0.038 0.038 0.270 0.270
## 64 V_verbal =~ Cadri29a 19.976 0.443 0.159 0.412 0.412
## 271 Cadri23a ~~ Cadri35a 18.853 0.034 0.034 0.256 0.256
## 114 V_relaci =~ Cadri21a 17.628 1.987 0.252 0.519 0.519
## 123 V_relaci =~ Cadri29a 15.500 1.024 0.130 0.338 0.338
## 85 V_fisica =~ Cadri3a 15.126 0.420 0.109 0.278 0.278
## 84 V_fisica =~ Cadri33a 14.554 0.470 0.122 0.456 0.456
## 88 V_fisica =~ Cadri2a 14.066 -0.892 -0.231 -0.513 -0.513
fit03_b <- cfa(model = model03,
data = cadri_data,
ordered = TRUE,
estimator = "WLSMV",
mimic = "Mplus")## Warning in lav_model_vcov(lavmodel = lavmodel, lavsamplestats = lavsamplestats, : lavaan WARNING:
## The variance-covariance matrix of the estimated parameters (vcov)
## does not appear to be positive definite! The smallest eigenvalue
## (= -6.588562e-17) is smaller than zero. This may be a symptom that
## the model is not identified.
## Warning in lav_object_post_check(object): lavaan WARNING: covariance matrix of latent variables
## is not positive definite;
## use lavInspect(fit, "cov.lv") to investigate.
## lavaan 0.6-6 ended normally after 55 iterations
##
## Estimator DWLS
## Optimization method NLMINB
## Number of free parameters 96
##
## Number of observations 326
##
## Model Test User Model:
## Standard Robust
## Test Statistic 295.580 321.481
## Degrees of freedom 199 199
## P-value (Chi-square) 0.000 0.000
## Scaling correction factor 1.346
## Shift parameter 101.852
## simple second-order correction (WLSMV)
##
## Model Test Baseline Model:
##
## Test statistic 7432.070 2947.528
## Degrees of freedom 231 231
## P-value 0.000 0.000
## Scaling correction factor 2.651
##
## User Model versus Baseline Model:
##
## Comparative Fit Index (CFI) 0.987 0.955
## Tucker-Lewis Index (TLI) 0.984 0.948
##
## Robust Comparative Fit Index (CFI) NA
## Robust Tucker-Lewis Index (TLI) NA
##
## Root Mean Square Error of Approximation:
##
## RMSEA 0.039 0.044
## 90 Percent confidence interval - lower 0.029 0.035
## 90 Percent confidence interval - upper 0.048 0.052
## P-value RMSEA <= 0.05 0.983 0.890
##
## Robust RMSEA NA
## 90 Percent confidence interval - lower NA
## 90 Percent confidence interval - upper NA
##
## Standardized Root Mean Square Residual:
##
## SRMR 0.105 0.105
##
## Weighted Root Mean Square Residual:
##
## WRMR 1.001 1.001
##
## Parameter Estimates:
##
## Standard errors Robust.sem
## Information Expected
## Information saturated (h1) model Unstructured
##
## Latent Variables:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## V_verbal =~
## Cadri4a 1.000 0.534 0.534
## Cadri7a 1.410 0.131 10.752 0.000 0.754 0.754
## Cadri9a 1.225 0.126 9.701 0.000 0.655 0.655
## Cadri12a 1.386 0.145 9.547 0.000 0.741 0.741
## Cadri17a 1.541 0.156 9.866 0.000 0.824 0.824
## Cadri21a 1.250 0.152 8.231 0.000 0.668 0.668
## Cadri23a 1.038 0.139 7.493 0.000 0.555 0.555
## Cadri24a 1.247 0.119 10.485 0.000 0.667 0.667
## Cadri28a 1.319 0.133 9.893 0.000 0.705 0.705
## Cadri32a 1.389 0.136 10.216 0.000 0.743 0.743
## V_fisica =~
## Cadri8a 1.000 0.838 0.838
## Cadri25a 0.938 0.076 12.332 0.000 0.786 0.786
## Cadri30a 1.054 0.087 12.127 0.000 0.884 0.884
## Cadri34a 0.977 0.077 12.686 0.000 0.819 0.819
## C_amenaz =~
## Cadri29a 1.000 0.574 0.574
## Cadri31a 1.235 0.197 6.271 0.000 0.709 0.709
## Cadri33a 1.553 0.220 7.054 0.000 0.892 0.892
## V_relaci =~
## Cadri3a 1.000 0.618 0.618
## Cadri20a 1.309 0.211 6.201 0.000 0.809 0.809
## Cadri35a 1.108 0.166 6.678 0.000 0.685 0.685
## V_sexual =~
## Cadri2a 1.000 0.600 0.600
## Cadri19a 1.313 0.287 4.577 0.000 0.787 0.787
##
## Covariances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## V_verbal ~~
## V_fisica 0.332 0.043 7.658 0.000 0.741 0.741
## C_amenaz 0.272 0.039 6.880 0.000 0.885 0.885
## V_relaci 0.284 0.055 5.174 0.000 0.860 0.860
## V_sexual 0.152 0.040 3.828 0.000 0.475 0.475
## V_fisica ~~
## C_amenaz 0.477 0.061 7.804 0.000 0.991 0.991
## V_relaci 0.257 0.075 3.430 0.001 0.495 0.495
## V_sexual 0.271 0.062 4.402 0.000 0.540 0.540
## C_amenaz ~~
## V_relaci 0.282 0.055 5.164 0.000 0.796 0.796
## V_sexual 0.259 0.066 3.930 0.000 0.753 0.753
## V_relaci ~~
## V_sexual 0.225 0.059 3.813 0.000 0.608 0.608
##
## Intercepts:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .Cadri4a 0.000 0.000 0.000
## .Cadri7a 0.000 0.000 0.000
## .Cadri9a 0.000 0.000 0.000
## .Cadri12a 0.000 0.000 0.000
## .Cadri17a 0.000 0.000 0.000
## .Cadri21a 0.000 0.000 0.000
## .Cadri23a 0.000 0.000 0.000
## .Cadri24a 0.000 0.000 0.000
## .Cadri28a 0.000 0.000 0.000
## .Cadri32a 0.000 0.000 0.000
## .Cadri8a 0.000 0.000 0.000
## .Cadri25a 0.000 0.000 0.000
## .Cadri30a 0.000 0.000 0.000
## .Cadri34a 0.000 0.000 0.000
## .Cadri29a 0.000 0.000 0.000
## .Cadri31a 0.000 0.000 0.000
## .Cadri33a 0.000 0.000 0.000
## .Cadri3a 0.000 0.000 0.000
## .Cadri20a 0.000 0.000 0.000
## .Cadri35a 0.000 0.000 0.000
## .Cadri2a 0.000 0.000 0.000
## .Cadri19a 0.000 0.000 0.000
## V_verbal 0.000 0.000 0.000
## V_fisica 0.000 0.000 0.000
## C_amenaz 0.000 0.000 0.000
## V_relaci 0.000 0.000 0.000
## V_sexual 0.000 0.000 0.000
##
## Thresholds:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## Cadri4a|t1 -0.069 0.070 -0.994 0.320 -0.069 -0.069
## Cadri4a|t2 1.035 0.085 12.173 0.000 1.035 1.035
## Cadri4a|t3 1.717 0.123 13.919 0.000 1.717 1.717
## Cadri7a|t1 0.178 0.070 2.539 0.011 0.178 0.178
## Cadri7a|t2 1.347 0.098 13.713 0.000 1.347 1.347
## Cadri7a|t3 1.717 0.123 13.919 0.000 1.717 1.717
## Cadri9a|t1 0.015 0.070 0.221 0.825 0.015 0.015
## Cadri9a|t2 1.177 0.090 13.029 0.000 1.177 1.177
## Cadri9a|t3 1.871 0.138 13.536 0.000 1.871 1.871
## Cadri12a|t1 0.549 0.074 7.465 0.000 0.549 0.549
## Cadri12a|t2 1.495 0.107 14.000 0.000 1.495 1.495
## Cadri12a|t3 1.871 0.138 13.536 0.000 1.871 1.871
## Cadri17a|t1 0.844 0.079 10.623 0.000 0.844 0.844
## Cadri17a|t2 1.654 0.118 14.003 0.000 1.654 1.654
## Cadri17a|t3 2.357 0.214 11.014 0.000 2.357 2.357
## Cadri21a|t1 1.089 0.087 12.530 0.000 1.089 1.089
## Cadri21a|t2 1.917 0.143 13.374 0.000 1.917 1.917
## Cadri21a|t3 2.357 0.214 11.014 0.000 2.357 2.357
## Cadri23a|t1 1.224 0.092 13.258 0.000 1.224 1.224
## Cadri23a|t2 2.088 0.166 12.614 0.000 2.088 2.088
## Cadri23a|t3 2.504 0.250 10.011 0.000 2.504 2.504
## Cadri24a|t1 0.445 0.072 6.162 0.000 0.445 0.445
## Cadri24a|t2 1.871 0.138 13.536 0.000 1.871 1.871
## Cadri24a|t3 2.357 0.214 11.014 0.000 2.357 2.357
## Cadri28a|t1 0.462 0.072 6.380 0.000 0.462 0.462
## Cadri28a|t2 1.177 0.090 13.029 0.000 1.177 1.177
## Cadri28a|t3 1.828 0.134 13.667 0.000 1.828 1.828
## Cadri32a|t1 0.622 0.075 8.324 0.000 0.622 0.622
## Cadri32a|t2 1.569 0.112 14.040 0.000 1.569 1.569
## Cadri32a|t3 1.828 0.134 13.667 0.000 1.828 1.828
## Cadri8a|t1 1.347 0.098 13.713 0.000 1.347 1.347
## Cadri8a|t2 2.161 0.177 12.220 0.000 2.161 2.161
## Cadri8a|t3 2.740 0.329 8.326 0.000 2.740 2.740
## Cadri25a|t1 1.257 0.094 13.400 0.000 1.257 1.257
## Cadri25a|t2 2.249 0.192 11.707 0.000 2.249 2.249
## Cadri30a|t1 1.257 0.094 13.400 0.000 1.257 1.257
## Cadri30a|t2 2.024 0.157 12.925 0.000 2.024 2.024
## Cadri30a|t3 2.504 0.250 10.011 0.000 2.504 2.504
## Cadri34a|t1 1.328 0.097 13.656 0.000 1.328 1.328
## Cadri34a|t2 2.249 0.192 11.707 0.000 2.249 2.249
## Cadri34a|t3 2.740 0.329 8.326 0.000 2.740 2.740
## Cadri29a|t1 1.292 0.095 13.534 0.000 1.292 1.292
## Cadri29a|t2 2.024 0.157 12.925 0.000 2.024 2.024
## Cadri31a|t1 2.161 0.177 12.220 0.000 2.161 2.161
## Cadri31a|t2 2.504 0.250 10.011 0.000 2.504 2.504
## Cadri31a|t3 2.740 0.329 8.326 0.000 2.740 2.740
## Cadri33a|t1 1.871 0.138 13.536 0.000 1.871 1.871
## Cadri33a|t2 2.357 0.214 11.014 0.000 2.357 2.357
## Cadri33a|t3 2.740 0.329 8.326 0.000 2.740 2.740
## Cadri3a|t1 1.472 0.105 13.974 0.000 1.472 1.472
## Cadri3a|t2 2.161 0.177 12.220 0.000 2.161 2.161
## Cadri3a|t3 2.357 0.214 11.014 0.000 2.357 2.357
## Cadri20a|t1 1.717 0.123 13.919 0.000 1.717 1.717
## Cadri20a|t2 2.161 0.177 12.220 0.000 2.161 2.161
## Cadri20a|t3 2.504 0.250 10.011 0.000 2.504 2.504
## Cadri35a|t1 1.347 0.098 13.713 0.000 1.347 1.347
## Cadri35a|t2 2.161 0.177 12.220 0.000 2.161 2.161
## Cadri35a|t3 2.504 0.250 10.011 0.000 2.504 2.504
## Cadri2a|t1 1.386 0.100 13.817 0.000 1.386 1.386
## Cadri2a|t2 1.968 0.149 13.174 0.000 1.968 1.968
## Cadri2a|t3 2.249 0.192 11.707 0.000 2.249 2.249
## Cadri19a|t1 0.558 0.074 7.573 0.000 0.558 0.558
## Cadri19a|t2 1.257 0.094 13.400 0.000 1.257 1.257
## Cadri19a|t3 1.789 0.130 13.772 0.000 1.789 1.789
##
## Variances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .Cadri4a 0.714 0.714 0.714
## .Cadri7a 0.432 0.432 0.432
## .Cadri9a 0.572 0.572 0.572
## .Cadri12a 0.451 0.451 0.451
## .Cadri17a 0.321 0.321 0.321
## .Cadri21a 0.554 0.554 0.554
## .Cadri23a 0.692 0.692 0.692
## .Cadri24a 0.556 0.556 0.556
## .Cadri28a 0.503 0.503 0.503
## .Cadri32a 0.449 0.449 0.449
## .Cadri8a 0.297 0.297 0.297
## .Cadri25a 0.382 0.382 0.382
## .Cadri30a 0.219 0.219 0.219
## .Cadri34a 0.329 0.329 0.329
## .Cadri29a 0.670 0.670 0.670
## .Cadri31a 0.497 0.497 0.497
## .Cadri33a 0.205 0.205 0.205
## .Cadri3a 0.618 0.618 0.618
## .Cadri20a 0.346 0.346 0.346
## .Cadri35a 0.531 0.531 0.531
## .Cadri2a 0.640 0.640 0.640
## .Cadri19a 0.380 0.380 0.380
## V_verbal 0.286 0.054 5.324 0.000 1.000 1.000
## V_fisica 0.703 0.074 9.472 0.000 1.000 1.000
## C_amenaz 0.330 0.070 4.724 0.000 1.000 1.000
## V_relaci 0.382 0.097 3.921 0.000 1.000 1.000
## V_sexual 0.360 0.104 3.465 0.001 1.000 1.000
##
## Scales y*:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## Cadri4a 1.000 1.000 1.000
## Cadri7a 1.000 1.000 1.000
## Cadri9a 1.000 1.000 1.000
## Cadri12a 1.000 1.000 1.000
## Cadri17a 1.000 1.000 1.000
## Cadri21a 1.000 1.000 1.000
## Cadri23a 1.000 1.000 1.000
## Cadri24a 1.000 1.000 1.000
## Cadri28a 1.000 1.000 1.000
## Cadri32a 1.000 1.000 1.000
## Cadri8a 1.000 1.000 1.000
## Cadri25a 1.000 1.000 1.000
## Cadri30a 1.000 1.000 1.000
## Cadri34a 1.000 1.000 1.000
## Cadri29a 1.000 1.000 1.000
## Cadri31a 1.000 1.000 1.000
## Cadri33a 1.000 1.000 1.000
## Cadri3a 1.000 1.000 1.000
## Cadri20a 1.000 1.000 1.000
## Cadri35a 1.000 1.000 1.000
## Cadri2a 1.000 1.000 1.000
## Cadri19a 1.000 1.000 1.000
## Graficar
semPlot::semPaths(fit03_b, whatLabels = "std", label.cex= 1.2,
edge.label.cex = 0.8, nCharEdges = 3,
nCharNodes = 8, sizeLat = 7, sizeLat2 = 4,
sizeMan = 7, sizeMan2 = 2.5, rotation = 2, intercepts = F,
thresholds = F, groups = "latents", pastel = TRUE,
exoVar = FALSE, edge.color = "black",
curvature = 2, mar = c(1, 15, 2, 15), residScale = 10,
manifests = rev(fit03_b@Data@ordered))
title("Modelo Factorial del CADRI \n Modelo 03")Análisis del modelo 02 y 03
Conducta amenzante (Correlación mayor a 1): Violencia verbal, física y amenzante
Se mantienen los cambios del Modelo 02 y 03: - Sin item 15, 13 (V Sexual) - Sin item 05 (Conducta amenzante) - No considerar al factor Resolución de conflictos como parte del modelo factorial
Se adiciona el siguiente cambio: - Sin item 04 y 23 (V. Verbal) - Sin item 03 (V. relacional)
model04 <- "# Modelo de medición
V_verbal =~ Cadri7a + Cadri9a + Cadri12a + Cadri17a + Cadri21a +
Cadri24a + Cadri28a + Cadri32a
V_fisica =~ Cadri8a + Cadri25a + Cadri30a + Cadri34a
C_amenaz =~ Cadri29a + Cadri31a + Cadri33a
V_relaci =~ Cadri20a + Cadri35a
V_sexual =~ Cadri2a + Cadri19a"## Warning in lav_object_post_check(object): lavaan WARNING: covariance matrix of latent variables
## is not positive definite;
## use lavInspect(fit, "cov.lv") to investigate.
## lavaan 0.6-6 ended normally after 191 iterations
##
## Estimator ML
## Optimization method NLMINB
## Number of free parameters 48
##
## Number of observations 326
##
## Model Test User Model:
## Standard Robust
## Test Statistic 445.926 268.488
## Degrees of freedom 142 142
## P-value (Chi-square) 0.000 0.000
## Scaling correction factor 1.661
## Yuan-Bentler correction (Mplus variant)
##
## Model Test Baseline Model:
##
## Test statistic 1937.884 987.012
## Degrees of freedom 171 171
## P-value 0.000 0.000
## Scaling correction factor 1.963
##
## User Model versus Baseline Model:
##
## Comparative Fit Index (CFI) 0.828 0.845
## Tucker-Lewis Index (TLI) 0.793 0.813
##
## Robust Comparative Fit Index (CFI) 0.869
## Robust Tucker-Lewis Index (TLI) 0.842
##
## Loglikelihood and Information Criteria:
##
## Loglikelihood user model (H0) -3465.899 -3465.899
## Scaling correction factor 6.492
## for the MLR correction
## Loglikelihood unrestricted model (H1) -3242.936 -3242.936
## Scaling correction factor 2.881
## for the MLR correction
##
## Akaike (AIC) 7027.798 7027.798
## Bayesian (BIC) 7209.570 7209.570
## Sample-size adjusted Bayesian (BIC) 7057.317 7057.317
##
## Root Mean Square Error of Approximation:
##
## RMSEA 0.081 0.052
## 90 Percent confidence interval - lower 0.073 0.045
## 90 Percent confidence interval - upper 0.090 0.060
## P-value RMSEA <= 0.05 0.000 0.300
##
## Robust RMSEA 0.067
## 90 Percent confidence interval - lower 0.055
## 90 Percent confidence interval - upper 0.080
##
## Standardized Root Mean Square Residual:
##
## SRMR 0.069 0.069
##
## Parameter Estimates:
##
## Standard errors Sandwich
## Information bread Observed
## Observed information based on Hessian
##
## Latent Variables:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## V_verbal =~
## Cadri7a 1.000 0.540 0.699
## Cadri9a 0.755 0.103 7.346 0.000 0.407 0.530
## Cadri12a 0.889 0.097 9.115 0.000 0.480 0.681
## Cadri17a 0.756 0.084 9.026 0.000 0.408 0.715
## Cadri21a 0.440 0.110 4.014 0.000 0.238 0.489
## Cadri24a 0.636 0.099 6.427 0.000 0.343 0.597
## Cadri28a 0.911 0.098 9.266 0.000 0.491 0.622
## Cadri32a 0.869 0.091 9.525 0.000 0.469 0.676
## V_fisica =~
## Cadri8a 1.000 0.257 0.690
## Cadri25a 0.760 0.231 3.283 0.001 0.195 0.547
## Cadri30a 1.236 0.299 4.130 0.000 0.318 0.745
## Cadri34a 0.894 0.226 3.951 0.000 0.230 0.631
## C_amenaz =~
## Cadri29a 1.000 0.109 0.283
## Cadri31a 0.747 0.764 0.977 0.329 0.081 0.370
## Cadri33a 1.407 1.247 1.128 0.259 0.154 0.573
## V_relaci =~
## Cadri20a 1.000 0.196 0.575
## Cadri35a 1.098 0.410 2.680 0.007 0.215 0.548
## V_sexual =~
## Cadri2a 1.000 0.201 0.446
## Cadri19a 2.218 2.076 1.069 0.285 0.446 0.576
##
## Covariances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## V_verbal ~~
## V_fisica 0.086 0.032 2.696 0.007 0.620 0.620
## C_amenaz 0.042 0.034 1.245 0.213 0.720 0.720
## V_relaci 0.077 0.036 2.140 0.032 0.727 0.727
## V_sexual 0.046 0.028 1.636 0.102 0.421 0.421
## V_fisica ~~
## C_amenaz 0.030 0.018 1.604 0.109 1.055 1.055
## V_relaci 0.011 0.009 1.126 0.260 0.210 0.210
## V_sexual 0.026 0.013 2.016 0.044 0.494 0.494
## C_amenaz ~~
## V_relaci 0.013 0.010 1.309 0.191 0.626 0.626
## V_sexual 0.011 0.015 0.769 0.442 0.514 0.514
## V_relaci ~~
## V_sexual 0.017 0.021 0.783 0.434 0.422 0.422
##
## Variances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .Cadri7a 0.305 0.036 8.460 0.000 0.305 0.511
## .Cadri9a 0.425 0.049 8.604 0.000 0.425 0.719
## .Cadri12a 0.266 0.042 6.395 0.000 0.266 0.536
## .Cadri17a 0.160 0.023 6.804 0.000 0.160 0.489
## .Cadri21a 0.180 0.034 5.260 0.000 0.180 0.761
## .Cadri24a 0.213 0.024 8.882 0.000 0.213 0.644
## .Cadri28a 0.382 0.044 8.705 0.000 0.382 0.613
## .Cadri32a 0.262 0.039 6.789 0.000 0.262 0.543
## .Cadri8a 0.073 0.015 4.694 0.000 0.073 0.524
## .Cadri25a 0.089 0.020 4.409 0.000 0.089 0.701
## .Cadri30a 0.081 0.028 2.923 0.003 0.081 0.445
## .Cadri34a 0.080 0.023 3.542 0.000 0.080 0.602
## .Cadri29a 0.136 0.026 5.215 0.000 0.136 0.920
## .Cadri31a 0.042 0.026 1.618 0.106 0.042 0.863
## .Cadri33a 0.048 0.026 1.865 0.062 0.048 0.671
## .Cadri20a 0.077 0.030 2.580 0.010 0.077 0.669
## .Cadri35a 0.107 0.030 3.629 0.000 0.107 0.700
## .Cadri2a 0.163 0.045 3.590 0.000 0.163 0.801
## .Cadri19a 0.402 0.197 2.035 0.042 0.402 0.669
## V_verbal 0.291 0.059 4.960 0.000 1.000 1.000
## V_fisica 0.066 0.031 2.101 0.036 1.000 1.000
## C_amenaz 0.012 0.011 1.080 0.280 1.000 1.000
## V_relaci 0.038 0.025 1.501 0.133 1.000 1.000
## V_sexual 0.040 0.039 1.034 0.301 1.000 1.000
## Warning in lav_start_check_cov(lavpartable = lavpartable, start = START): lavaan WARNING: starting values imply a correlation larger than 1;
## variables involved are: V_fisica C_amenaz
## lhs op rhs mi epc sepc.lv sepc.all sepc.nox
## 267 Cadri30a ~~ Cadri31a 40.359 0.025 0.025 0.428 0.428
## 100 V_relaci =~ Cadri21a 32.546 1.596 0.312 0.642 0.642
## 251 Cadri8a ~~ Cadri33a 25.734 0.021 0.021 0.353 0.353
## 281 Cadri29a ~~ Cadri33a 24.610 -0.028 -0.028 -0.341 -0.341
## 110 V_relaci =~ Cadri33a 22.462 -0.724 -0.142 -0.528 -0.528
## 58 V_verbal =~ Cadri29a 21.274 0.306 0.165 0.429 0.429
## 98 V_relaci =~ Cadri12a 19.904 -1.604 -0.314 -0.446 -0.446
## 207 Cadri21a ~~ Cadri35a 17.833 0.036 0.036 0.260 0.260
## 108 V_relaci =~ Cadri29a 16.661 0.654 0.128 0.332 0.332
## 206 Cadri21a ~~ Cadri20a 16.475 0.030 0.030 0.253 0.253
## 78 V_fisica =~ Cadri2a 14.283 -1.062 -0.273 -0.605 -0.605
## 293 Cadri33a ~~ Cadri2a 13.037 -0.021 -0.021 -0.242 -0.242
## 79 V_fisica =~ Cadri19a 12.660 2.389 0.614 0.792 0.792
## 289 Cadri31a ~~ Cadri2a 11.912 0.017 0.017 0.212 0.212
## 287 Cadri31a ~~ Cadri20a 11.898 0.013 0.013 0.223 0.223
## 125 V_sexual =~ Cadri29a 10.685 0.676 0.136 0.353 0.353
## 190 Cadri17a ~~ Cadri31a 10.627 0.016 0.016 0.199 0.199
## 250 Cadri8a ~~ Cadri31a 10.209 -0.011 -0.011 -0.205 -0.205
## 298 Cadri35a ~~ Cadri2a 10.038 0.029 0.029 0.215 0.215
## 283 Cadri29a ~~ Cadri35a 9.740 0.023 0.023 0.194 0.194
fit04_b <- cfa(model = model04,
data = cadri_data,
ordered = TRUE,
estimator = "WLSMV",
mimic = "Mplus")## Warning in lav_model_vcov(lavmodel = lavmodel, lavsamplestats = lavsamplestats, : lavaan WARNING:
## The variance-covariance matrix of the estimated parameters (vcov)
## does not appear to be positive definite! The smallest eigenvalue
## (= -3.944463e-17) is smaller than zero. This may be a symptom that
## the model is not identified.
## Warning in lav_object_post_check(object): lavaan WARNING: covariance matrix of latent variables
## is not positive definite;
## use lavInspect(fit, "cov.lv") to investigate.
## lavaan 0.6-6 ended normally after 48 iterations
##
## Estimator DWLS
## Optimization method NLMINB
## Number of free parameters 84
##
## Number of observations 326
##
## Model Test User Model:
## Standard Robust
## Test Statistic 164.755 205.232
## Degrees of freedom 142 142
## P-value (Chi-square) 0.093 0.000
## Scaling correction factor 1.192
## Shift parameter 67.055
## simple second-order correction (WLSMV)
##
## Model Test Baseline Model:
##
## Test statistic 6323.983 2674.620
## Degrees of freedom 171 171
## P-value 0.000 0.000
## Scaling correction factor 2.458
##
## User Model versus Baseline Model:
##
## Comparative Fit Index (CFI) 0.996 0.975
## Tucker-Lewis Index (TLI) 0.996 0.970
##
## Robust Comparative Fit Index (CFI) NA
## Robust Tucker-Lewis Index (TLI) NA
##
## Root Mean Square Error of Approximation:
##
## RMSEA 0.022 0.037
## 90 Percent confidence interval - lower 0.000 0.025
## 90 Percent confidence interval - upper 0.036 0.048
## P-value RMSEA <= 0.05 1.000 0.978
##
## Robust RMSEA NA
## 90 Percent confidence interval - lower NA
## 90 Percent confidence interval - upper NA
##
## Standardized Root Mean Square Residual:
##
## SRMR 0.094 0.094
##
## Weighted Root Mean Square Residual:
##
## WRMR 0.854 0.854
##
## Parameter Estimates:
##
## Standard errors Robust.sem
## Information Expected
## Information saturated (h1) model Unstructured
##
## Latent Variables:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## V_verbal =~
## Cadri7a 1.000 0.736 0.736
## Cadri9a 0.868 0.071 12.179 0.000 0.639 0.639
## Cadri12a 1.037 0.066 15.669 0.000 0.763 0.763
## Cadri17a 1.139 0.070 16.343 0.000 0.838 0.838
## Cadri21a 0.916 0.085 10.783 0.000 0.674 0.674
## Cadri24a 0.917 0.061 14.936 0.000 0.674 0.674
## Cadri28a 0.949 0.068 13.987 0.000 0.698 0.698
## Cadri32a 0.997 0.063 15.790 0.000 0.734 0.734
## V_fisica =~
## Cadri8a 1.000 0.840 0.840
## Cadri25a 0.937 0.075 12.504 0.000 0.787 0.787
## Cadri30a 1.049 0.087 12.100 0.000 0.881 0.881
## Cadri34a 0.978 0.076 12.802 0.000 0.821 0.821
## C_amenaz =~
## Cadri29a 1.000 0.569 0.569
## Cadri31a 1.240 0.205 6.040 0.000 0.706 0.706
## Cadri33a 1.593 0.224 7.118 0.000 0.907 0.907
## V_relaci =~
## Cadri20a 1.000 0.846 0.846
## Cadri35a 0.853 0.108 7.926 0.000 0.721 0.721
## V_sexual =~
## Cadri2a 1.000 0.602 0.602
## Cadri19a 1.303 0.286 4.559 0.000 0.785 0.785
##
## Covariances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## V_verbal ~~
## V_fisica 0.464 0.049 9.515 0.000 0.752 0.752
## C_amenaz 0.373 0.049 7.662 0.000 0.892 0.892
## V_relaci 0.509 0.069 7.434 0.000 0.819 0.819
## V_sexual 0.203 0.053 3.842 0.000 0.459 0.459
## V_fisica ~~
## C_amenaz 0.469 0.061 7.725 0.000 0.981 0.981
## V_relaci 0.271 0.108 2.502 0.012 0.381 0.381
## V_sexual 0.273 0.062 4.383 0.000 0.541 0.541
## C_amenaz ~~
## V_relaci 0.317 0.059 5.357 0.000 0.659 0.659
## V_sexual 0.257 0.065 3.962 0.000 0.752 0.752
## V_relaci ~~
## V_sexual 0.285 0.070 4.069 0.000 0.559 0.559
##
## Intercepts:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .Cadri7a 0.000 0.000 0.000
## .Cadri9a 0.000 0.000 0.000
## .Cadri12a 0.000 0.000 0.000
## .Cadri17a 0.000 0.000 0.000
## .Cadri21a 0.000 0.000 0.000
## .Cadri24a 0.000 0.000 0.000
## .Cadri28a 0.000 0.000 0.000
## .Cadri32a 0.000 0.000 0.000
## .Cadri8a 0.000 0.000 0.000
## .Cadri25a 0.000 0.000 0.000
## .Cadri30a 0.000 0.000 0.000
## .Cadri34a 0.000 0.000 0.000
## .Cadri29a 0.000 0.000 0.000
## .Cadri31a 0.000 0.000 0.000
## .Cadri33a 0.000 0.000 0.000
## .Cadri20a 0.000 0.000 0.000
## .Cadri35a 0.000 0.000 0.000
## .Cadri2a 0.000 0.000 0.000
## .Cadri19a 0.000 0.000 0.000
## V_verbal 0.000 0.000 0.000
## V_fisica 0.000 0.000 0.000
## C_amenaz 0.000 0.000 0.000
## V_relaci 0.000 0.000 0.000
## V_sexual 0.000 0.000 0.000
##
## Thresholds:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## Cadri7a|t1 0.178 0.070 2.539 0.011 0.178 0.178
## Cadri7a|t2 1.347 0.098 13.713 0.000 1.347 1.347
## Cadri7a|t3 1.717 0.123 13.919 0.000 1.717 1.717
## Cadri9a|t1 0.015 0.070 0.221 0.825 0.015 0.015
## Cadri9a|t2 1.177 0.090 13.029 0.000 1.177 1.177
## Cadri9a|t3 1.871 0.138 13.536 0.000 1.871 1.871
## Cadri12a|t1 0.549 0.074 7.465 0.000 0.549 0.549
## Cadri12a|t2 1.495 0.107 14.000 0.000 1.495 1.495
## Cadri12a|t3 1.871 0.138 13.536 0.000 1.871 1.871
## Cadri17a|t1 0.844 0.079 10.623 0.000 0.844 0.844
## Cadri17a|t2 1.654 0.118 14.003 0.000 1.654 1.654
## Cadri17a|t3 2.357 0.214 11.014 0.000 2.357 2.357
## Cadri21a|t1 1.089 0.087 12.530 0.000 1.089 1.089
## Cadri21a|t2 1.917 0.143 13.374 0.000 1.917 1.917
## Cadri21a|t3 2.357 0.214 11.014 0.000 2.357 2.357
## Cadri24a|t1 0.445 0.072 6.162 0.000 0.445 0.445
## Cadri24a|t2 1.871 0.138 13.536 0.000 1.871 1.871
## Cadri24a|t3 2.357 0.214 11.014 0.000 2.357 2.357
## Cadri28a|t1 0.462 0.072 6.380 0.000 0.462 0.462
## Cadri28a|t2 1.177 0.090 13.029 0.000 1.177 1.177
## Cadri28a|t3 1.828 0.134 13.667 0.000 1.828 1.828
## Cadri32a|t1 0.622 0.075 8.324 0.000 0.622 0.622
## Cadri32a|t2 1.569 0.112 14.040 0.000 1.569 1.569
## Cadri32a|t3 1.828 0.134 13.667 0.000 1.828 1.828
## Cadri8a|t1 1.347 0.098 13.713 0.000 1.347 1.347
## Cadri8a|t2 2.161 0.177 12.220 0.000 2.161 2.161
## Cadri8a|t3 2.740 0.329 8.326 0.000 2.740 2.740
## Cadri25a|t1 1.257 0.094 13.400 0.000 1.257 1.257
## Cadri25a|t2 2.249 0.192 11.707 0.000 2.249 2.249
## Cadri30a|t1 1.257 0.094 13.400 0.000 1.257 1.257
## Cadri30a|t2 2.024 0.157 12.925 0.000 2.024 2.024
## Cadri30a|t3 2.504 0.250 10.011 0.000 2.504 2.504
## Cadri34a|t1 1.328 0.097 13.656 0.000 1.328 1.328
## Cadri34a|t2 2.249 0.192 11.707 0.000 2.249 2.249
## Cadri34a|t3 2.740 0.329 8.326 0.000 2.740 2.740
## Cadri29a|t1 1.292 0.095 13.534 0.000 1.292 1.292
## Cadri29a|t2 2.024 0.157 12.925 0.000 2.024 2.024
## Cadri31a|t1 2.161 0.177 12.220 0.000 2.161 2.161
## Cadri31a|t2 2.504 0.250 10.011 0.000 2.504 2.504
## Cadri31a|t3 2.740 0.329 8.326 0.000 2.740 2.740
## Cadri33a|t1 1.871 0.138 13.536 0.000 1.871 1.871
## Cadri33a|t2 2.357 0.214 11.014 0.000 2.357 2.357
## Cadri33a|t3 2.740 0.329 8.326 0.000 2.740 2.740
## Cadri20a|t1 1.717 0.123 13.919 0.000 1.717 1.717
## Cadri20a|t2 2.161 0.177 12.220 0.000 2.161 2.161
## Cadri20a|t3 2.504 0.250 10.011 0.000 2.504 2.504
## Cadri35a|t1 1.347 0.098 13.713 0.000 1.347 1.347
## Cadri35a|t2 2.161 0.177 12.220 0.000 2.161 2.161
## Cadri35a|t3 2.504 0.250 10.011 0.000 2.504 2.504
## Cadri2a|t1 1.386 0.100 13.817 0.000 1.386 1.386
## Cadri2a|t2 1.968 0.149 13.174 0.000 1.968 1.968
## Cadri2a|t3 2.249 0.192 11.707 0.000 2.249 2.249
## Cadri19a|t1 0.558 0.074 7.573 0.000 0.558 0.558
## Cadri19a|t2 1.257 0.094 13.400 0.000 1.257 1.257
## Cadri19a|t3 1.789 0.130 13.772 0.000 1.789 1.789
##
## Variances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .Cadri7a 0.459 0.459 0.459
## .Cadri9a 0.592 0.592 0.592
## .Cadri12a 0.418 0.418 0.418
## .Cadri17a 0.298 0.298 0.298
## .Cadri21a 0.546 0.546 0.546
## .Cadri24a 0.545 0.545 0.545
## .Cadri28a 0.513 0.513 0.513
## .Cadri32a 0.462 0.462 0.462
## .Cadri8a 0.295 0.295 0.295
## .Cadri25a 0.381 0.381 0.381
## .Cadri30a 0.225 0.225 0.225
## .Cadri34a 0.326 0.326 0.326
## .Cadri29a 0.676 0.676 0.676
## .Cadri31a 0.502 0.502 0.502
## .Cadri33a 0.178 0.178 0.178
## .Cadri20a 0.285 0.285 0.285
## .Cadri35a 0.480 0.480 0.480
## .Cadri2a 0.638 0.638 0.638
## .Cadri19a 0.384 0.384 0.384
## V_verbal 0.541 0.052 10.483 0.000 1.000 1.000
## V_fisica 0.705 0.074 9.486 0.000 1.000 1.000
## C_amenaz 0.324 0.071 4.582 0.000 1.000 1.000
## V_relaci 0.715 0.147 4.883 0.000 1.000 1.000
## V_sexual 0.362 0.106 3.413 0.001 1.000 1.000
##
## Scales y*:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## Cadri7a 1.000 1.000 1.000
## Cadri9a 1.000 1.000 1.000
## Cadri12a 1.000 1.000 1.000
## Cadri17a 1.000 1.000 1.000
## Cadri21a 1.000 1.000 1.000
## Cadri24a 1.000 1.000 1.000
## Cadri28a 1.000 1.000 1.000
## Cadri32a 1.000 1.000 1.000
## Cadri8a 1.000 1.000 1.000
## Cadri25a 1.000 1.000 1.000
## Cadri30a 1.000 1.000 1.000
## Cadri34a 1.000 1.000 1.000
## Cadri29a 1.000 1.000 1.000
## Cadri31a 1.000 1.000 1.000
## Cadri33a 1.000 1.000 1.000
## Cadri20a 1.000 1.000 1.000
## Cadri35a 1.000 1.000 1.000
## Cadri2a 1.000 1.000 1.000
## Cadri19a 1.000 1.000 1.000
## lhs op rhs mi epc sepc.lv sepc.all sepc.nox
## 171 V_fisica =~ Cadri29a 20.335 -1.826 -1.533 -1.533 -1.533
## 206 V_relaci =~ Cadri29a 20.061 0.745 0.630 0.630 0.630
## 386 Cadri31a ~~ Cadri35a 17.083 -0.307 -0.307 -0.626 -0.626
## 198 V_relaci =~ Cadri21a 16.360 0.814 0.688 0.688 0.688
## 305 Cadri21a ~~ Cadri35a 15.029 0.314 0.314 0.613 0.613
## 156 V_verbal =~ Cadri29a 14.186 1.098 0.808 0.808 0.808
## 196 V_relaci =~ Cadri12a 12.012 -0.656 -0.555 -0.555 -0.555
## 381 Cadri29a ~~ Cadri35a 8.699 0.319 0.319 0.561 0.561
## 167 V_fisica =~ Cadri21a 8.351 -0.452 -0.380 -0.380 -0.380
## 257 Cadri9a ~~ Cadri31a 7.913 0.285 0.285 0.523 0.523
## 385 Cadri31a ~~ Cadri20a 7.730 0.284 0.284 0.751 0.751
## 304 Cadri21a ~~ Cadri20a 7.646 0.249 0.249 0.633 0.633
## 384 Cadri31a ~~ Cadri33a 7.318 0.320 0.320 1.071 1.071
## 173 V_fisica =~ Cadri33a 6.248 1.247 1.047 1.047 1.047
## 365 Cadri30a ~~ Cadri31a 6.042 0.233 0.233 0.693 0.693
## 177 V_fisica =~ Cadri19a 5.566 0.800 0.672 0.672 0.672
## 176 V_fisica =~ Cadri2a 5.566 -0.614 -0.515 -0.515 -0.515
## 165 V_fisica =~ Cadri12a 5.236 0.294 0.246 0.246 0.246
## 256 Cadri9a ~~ Cadri29a 5.112 0.216 0.216 0.341 0.341
## 157 V_verbal =~ Cadri31a 4.995 -0.623 -0.458 -0.458 -0.458
semPlot::semPaths(fit04_b, whatLabels = "std", label.cex= 1.3,
edge.label.cex = 0.8, nCharEdges = 3,
nCharNodes = 8, sizeLat = 7, sizeLat2 = 4,
sizeMan = 7, sizeMan2 = 2.8, rotation = 2, intercepts = F,
thresholds = F, groups = "latents", pastel = TRUE,
exoVar = FALSE, edge.color = "black",
curvature = 2, mar = c(1, 15, 2, 15), residScale = 10,
manifests = rev(fit04_b@Data@ordered))
title("Modelo Factorial del CADRI \n Modelo 04")Se mantienen los cambios de los modelos anteriores - Sin item 15, 13 (V Sexual) - Sin item 05 (Conducta amenzante) - No considerar al factor Resolución de conflictos como parte del modelo factorial - Sin item 04 y 23 (V. Verbal) - Sin item 03 (V. relacional)
Se incorpora los cambios que se encontrarán en el modelo 07 posteriormente: - Teórica y empíricamente el ítem 21 afecta directamente a las relaciones de la persona - Quitar el ítem 29. Presenta carga compuesta
model04_fork <- "# Modelo de medición
V_verbal =~ Cadri7a + Cadri9a + Cadri12a + Cadri17a +
Cadri24a + Cadri28a + Cadri32a
V_fisica =~ Cadri8a + Cadri25a + Cadri30a + Cadri34a
C_amenaz =~ Cadri31a + Cadri33a
V_relaci =~ Cadri20a + Cadri21a + Cadri35a
V_sexual =~ Cadri2a + Cadri19a"fit04_a_fork <- cfa(model = model04_fork,
data = cadri_data,
estimator = "MLR")
summary(fit04_a_fork, fit.measures = TRUE, standardized = TRUE)## lavaan 0.6-6 ended normally after 140 iterations
##
## Estimator ML
## Optimization method NLMINB
## Number of free parameters 46
##
## Number of observations 326
##
## Model Test User Model:
## Standard Robust
## Test Statistic 329.398 201.886
## Degrees of freedom 125 125
## P-value (Chi-square) 0.000 0.000
## Scaling correction factor 1.632
## Yuan-Bentler correction (Mplus variant)
##
## Model Test Baseline Model:
##
## Test statistic 1844.236 940.536
## Degrees of freedom 153 153
## P-value 0.000 0.000
## Scaling correction factor 1.961
##
## User Model versus Baseline Model:
##
## Comparative Fit Index (CFI) 0.879 0.902
## Tucker-Lewis Index (TLI) 0.852 0.881
##
## Robust Comparative Fit Index (CFI) 0.919
## Robust Tucker-Lewis Index (TLI) 0.901
##
## Loglikelihood and Information Criteria:
##
## Loglikelihood user model (H0) -3303.012 -3303.012
## Scaling correction factor 6.547
## for the MLR correction
## Loglikelihood unrestricted model (H1) -3138.313 -3138.313
## Scaling correction factor 2.954
## for the MLR correction
##
## Akaike (AIC) 6698.024 6698.024
## Bayesian (BIC) 6872.222 6872.222
## Sample-size adjusted Bayesian (BIC) 6726.312 6726.312
##
## Root Mean Square Error of Approximation:
##
## RMSEA 0.071 0.043
## 90 Percent confidence interval - lower 0.062 0.035
## 90 Percent confidence interval - upper 0.080 0.052
## P-value RMSEA <= 0.05 0.000 0.896
##
## Robust RMSEA 0.055
## 90 Percent confidence interval - lower 0.041
## 90 Percent confidence interval - upper 0.069
##
## Standardized Root Mean Square Residual:
##
## SRMR 0.056 0.056
##
## Parameter Estimates:
##
## Standard errors Sandwich
## Information bread Observed
## Observed information based on Hessian
##
## Latent Variables:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## V_verbal =~
## Cadri7a 1.000 0.541 0.701
## Cadri9a 0.755 0.102 7.386 0.000 0.409 0.531
## Cadri12a 0.901 0.099 9.058 0.000 0.487 0.692
## Cadri17a 0.753 0.085 8.827 0.000 0.407 0.713
## Cadri24a 0.630 0.098 6.395 0.000 0.341 0.592
## Cadri28a 0.913 0.102 8.993 0.000 0.494 0.625
## Cadri32a 0.873 0.091 9.559 0.000 0.472 0.681
## V_fisica =~
## Cadri8a 1.000 0.261 0.701
## Cadri25a 0.740 0.233 3.170 0.002 0.193 0.541
## Cadri30a 1.210 0.285 4.249 0.000 0.316 0.741
## Cadri34a 0.873 0.223 3.912 0.000 0.228 0.626
## C_amenaz =~
## Cadri31a 1.000 0.091 0.411
## Cadri33a 2.118 1.302 1.626 0.104 0.192 0.716
## V_relaci =~
## Cadri20a 1.000 0.202 0.595
## Cadri21a 1.671 0.401 4.162 0.000 0.338 0.695
## Cadri35a 1.110 0.389 2.855 0.004 0.224 0.573
## V_sexual =~
## Cadri2a 1.000 0.179 0.398
## Cadri19a 2.786 1.554 1.793 0.073 0.500 0.645
##
## Covariances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## V_verbal ~~
## V_fisica 0.089 0.033 2.737 0.006 0.631 0.631
## C_amenaz 0.025 0.018 1.436 0.151 0.517 0.517
## V_relaci 0.072 0.033 2.145 0.032 0.656 0.656
## V_sexual 0.040 0.021 1.902 0.057 0.408 0.408
## V_fisica ~~
## C_amenaz 0.021 0.013 1.580 0.114 0.900 0.900
## V_relaci 0.013 0.008 1.642 0.101 0.246 0.246
## V_sexual 0.022 0.011 2.067 0.039 0.478 0.478
## C_amenaz ~~
## V_relaci 0.007 0.006 1.096 0.273 0.385 0.385
## V_sexual 0.005 0.005 1.002 0.316 0.310 0.310
## V_relaci ~~
## V_sexual 0.010 0.008 1.269 0.204 0.284 0.284
##
## Variances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .Cadri7a 0.303 0.037 8.086 0.000 0.303 0.509
## .Cadri9a 0.424 0.049 8.611 0.000 0.424 0.718
## .Cadri12a 0.258 0.041 6.301 0.000 0.258 0.521
## .Cadri17a 0.160 0.024 6.614 0.000 0.160 0.491
## .Cadri24a 0.215 0.024 8.888 0.000 0.215 0.649
## .Cadri28a 0.380 0.044 8.606 0.000 0.380 0.609
## .Cadri32a 0.258 0.038 6.854 0.000 0.258 0.536
## .Cadri8a 0.071 0.015 4.724 0.000 0.071 0.508
## .Cadri25a 0.090 0.020 4.433 0.000 0.090 0.707
## .Cadri30a 0.082 0.028 2.932 0.003 0.082 0.451
## .Cadri34a 0.081 0.023 3.580 0.000 0.081 0.608
## .Cadri31a 0.040 0.025 1.593 0.111 0.040 0.831
## .Cadri33a 0.035 0.024 1.450 0.147 0.035 0.488
## .Cadri20a 0.075 0.028 2.621 0.009 0.075 0.646
## .Cadri21a 0.122 0.034 3.583 0.000 0.122 0.517
## .Cadri35a 0.103 0.030 3.435 0.001 0.103 0.672
## .Cadri2a 0.171 0.044 3.916 0.000 0.171 0.842
## .Cadri19a 0.351 0.161 2.184 0.029 0.351 0.584
## V_verbal 0.293 0.059 4.925 0.000 1.000 1.000
## V_fisica 0.068 0.032 2.108 0.035 1.000 1.000
## C_amenaz 0.008 0.009 0.875 0.382 1.000 1.000
## V_relaci 0.041 0.027 1.537 0.124 1.000 1.000
## V_sexual 0.032 0.021 1.556 0.120 1.000 1.000
## lhs op rhs mi epc sepc.lv sepc.all sepc.nox
## 242 Cadri30a ~~ Cadri31a 38.890 0.025 0.025 0.440 0.440
## 257 Cadri31a ~~ Cadri20a 20.229 0.015 0.015 0.281 0.281
## 226 Cadri8a ~~ Cadri33a 19.281 0.018 0.018 0.366 0.366
## 260 Cadri31a ~~ Cadri2a 17.512 0.021 0.021 0.251 0.251
## 225 Cadri8a ~~ Cadri31a 15.988 -0.014 -0.014 -0.268 -0.268
## 179 Cadri17a ~~ Cadri31a 14.624 0.019 0.019 0.235 0.235
## 274 Cadri35a ~~ Cadri2a 13.495 0.031 0.031 0.231 0.231
## 95 V_relaci =~ Cadri12a 10.853 -0.926 -0.187 -0.266 -0.266
## 249 Cadri34a ~~ Cadri31a 9.845 -0.011 -0.011 -0.198 -0.198
## 178 Cadri17a ~~ Cadri34a 9.421 -0.022 -0.022 -0.196 -0.196
## 265 Cadri33a ~~ Cadri2a 9.281 -0.017 -0.017 -0.217 -0.217
## 150 Cadri9a ~~ Cadri31a 8.957 0.023 0.023 0.175 0.175
## 116 V_sexual =~ Cadri25a 8.544 0.509 0.091 0.256 0.256
## 223 Cadri8a ~~ Cadri30a 8.351 -0.019 -0.019 -0.251 -0.251
## 87 C_amenaz =~ Cadri34a 7.847 -2.098 -0.190 -0.521 -0.521
## 258 Cadri31a ~~ Cadri21a 7.787 -0.013 -0.013 -0.189 -0.189
## 235 Cadri25a ~~ Cadri33a 7.456 -0.011 -0.011 -0.196 -0.196
## 97 V_relaci =~ Cadri24a 7.425 0.668 0.135 0.235 0.235
## 165 Cadri12a ~~ Cadri31a 7.192 -0.017 -0.017 -0.163 -0.163
## 233 Cadri25a ~~ Cadri34a 7.097 0.015 0.015 0.170 0.170
fit04_b_fork <- cfa(model = model04_fork,
data = cadri_data,
ordered = TRUE,
estimator = "WLSMV",
mimic = "Mplus")## Warning in lav_model_vcov(lavmodel = lavmodel, lavsamplestats = lavsamplestats, : lavaan WARNING:
## The variance-covariance matrix of the estimated parameters (vcov)
## does not appear to be positive definite! The smallest eigenvalue
## (= -4.288700e-17) is smaller than zero. This may be a symptom that
## the model is not identified.
## lavaan 0.6-6 ended normally after 37 iterations
##
## Estimator DWLS
## Optimization method NLMINB
## Number of free parameters 81
##
## Number of observations 326
##
## Model Test User Model:
## Standard Robust
## Test Statistic 107.159 153.954
## Degrees of freedom 125 125
## P-value (Chi-square) 0.874 0.040
## Scaling correction factor 1.100
## Shift parameter 56.530
## simple second-order correction (WLSMV)
##
## Model Test Baseline Model:
##
## Test statistic 6023.208 2620.833
## Degrees of freedom 153 153
## P-value 0.000 0.000
## Scaling correction factor 2.379
##
## User Model versus Baseline Model:
##
## Comparative Fit Index (CFI) 1.000 0.988
## Tucker-Lewis Index (TLI) 1.004 0.986
##
## Robust Comparative Fit Index (CFI) NA
## Robust Tucker-Lewis Index (TLI) NA
##
## Root Mean Square Error of Approximation:
##
## RMSEA 0.000 0.027
## 90 Percent confidence interval - lower 0.000 0.006
## 90 Percent confidence interval - upper 0.015 0.040
## P-value RMSEA <= 0.05 1.000 0.999
##
## Robust RMSEA NA
## 90 Percent confidence interval - lower NA
## 90 Percent confidence interval - upper NA
##
## Standardized Root Mean Square Residual:
##
## SRMR 0.080 0.080
##
## Weighted Root Mean Square Residual:
##
## WRMR 0.721 0.721
##
## Parameter Estimates:
##
## Standard errors Robust.sem
## Information Expected
## Information saturated (h1) model Unstructured
##
## Latent Variables:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## V_verbal =~
## Cadri7a 1.000 0.745 0.745
## Cadri9a 0.849 0.071 11.966 0.000 0.632 0.632
## Cadri12a 1.041 0.065 16.061 0.000 0.775 0.775
## Cadri17a 1.128 0.069 16.390 0.000 0.840 0.840
## Cadri24a 0.917 0.061 15.021 0.000 0.683 0.683
## Cadri28a 0.936 0.067 13.908 0.000 0.697 0.697
## Cadri32a 0.994 0.062 16.065 0.000 0.740 0.740
## V_fisica =~
## Cadri8a 1.000 0.839 0.839
## Cadri25a 0.934 0.073 12.798 0.000 0.784 0.784
## Cadri30a 1.051 0.084 12.543 0.000 0.882 0.882
## Cadri34a 0.981 0.075 13.016 0.000 0.823 0.823
## C_amenaz =~
## Cadri31a 1.000 0.780 0.780
## Cadri33a 1.229 0.156 7.880 0.000 0.959 0.959
## V_relaci =~
## Cadri20a 1.000 0.845 0.845
## Cadri21a 1.004 0.131 7.660 0.000 0.849 0.849
## Cadri35a 0.849 0.106 7.986 0.000 0.718 0.718
## V_sexual =~
## Cadri2a 1.000 0.596 0.596
## Cadri19a 1.329 0.288 4.620 0.000 0.792 0.792
##
## Covariances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## V_verbal ~~
## V_fisica 0.471 0.049 9.633 0.000 0.754 0.754
## C_amenaz 0.449 0.066 6.834 0.000 0.772 0.772
## V_relaci 0.459 0.068 6.719 0.000 0.730 0.730
## V_sexual 0.202 0.053 3.826 0.000 0.455 0.455
## V_fisica ~~
## C_amenaz 0.617 0.080 7.756 0.000 0.942 0.942
## V_relaci 0.316 0.088 3.612 0.000 0.446 0.446
## V_sexual 0.269 0.061 4.421 0.000 0.539 0.539
## C_amenaz ~~
## V_relaci 0.359 0.064 5.640 0.000 0.545 0.545
## V_sexual 0.318 0.061 5.212 0.000 0.683 0.683
## V_relaci ~~
## V_sexual 0.232 0.056 4.111 0.000 0.461 0.461
##
## Intercepts:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .Cadri7a 0.000 0.000 0.000
## .Cadri9a 0.000 0.000 0.000
## .Cadri12a 0.000 0.000 0.000
## .Cadri17a 0.000 0.000 0.000
## .Cadri24a 0.000 0.000 0.000
## .Cadri28a 0.000 0.000 0.000
## .Cadri32a 0.000 0.000 0.000
## .Cadri8a 0.000 0.000 0.000
## .Cadri25a 0.000 0.000 0.000
## .Cadri30a 0.000 0.000 0.000
## .Cadri34a 0.000 0.000 0.000
## .Cadri31a 0.000 0.000 0.000
## .Cadri33a 0.000 0.000 0.000
## .Cadri20a 0.000 0.000 0.000
## .Cadri21a 0.000 0.000 0.000
## .Cadri35a 0.000 0.000 0.000
## .Cadri2a 0.000 0.000 0.000
## .Cadri19a 0.000 0.000 0.000
## V_verbal 0.000 0.000 0.000
## V_fisica 0.000 0.000 0.000
## C_amenaz 0.000 0.000 0.000
## V_relaci 0.000 0.000 0.000
## V_sexual 0.000 0.000 0.000
##
## Thresholds:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## Cadri7a|t1 0.178 0.070 2.539 0.011 0.178 0.178
## Cadri7a|t2 1.347 0.098 13.713 0.000 1.347 1.347
## Cadri7a|t3 1.717 0.123 13.919 0.000 1.717 1.717
## Cadri9a|t1 0.015 0.070 0.221 0.825 0.015 0.015
## Cadri9a|t2 1.177 0.090 13.029 0.000 1.177 1.177
## Cadri9a|t3 1.871 0.138 13.536 0.000 1.871 1.871
## Cadri12a|t1 0.549 0.074 7.465 0.000 0.549 0.549
## Cadri12a|t2 1.495 0.107 14.000 0.000 1.495 1.495
## Cadri12a|t3 1.871 0.138 13.536 0.000 1.871 1.871
## Cadri17a|t1 0.844 0.079 10.623 0.000 0.844 0.844
## Cadri17a|t2 1.654 0.118 14.003 0.000 1.654 1.654
## Cadri17a|t3 2.357 0.214 11.014 0.000 2.357 2.357
## Cadri24a|t1 0.445 0.072 6.162 0.000 0.445 0.445
## Cadri24a|t2 1.871 0.138 13.536 0.000 1.871 1.871
## Cadri24a|t3 2.357 0.214 11.014 0.000 2.357 2.357
## Cadri28a|t1 0.462 0.072 6.380 0.000 0.462 0.462
## Cadri28a|t2 1.177 0.090 13.029 0.000 1.177 1.177
## Cadri28a|t3 1.828 0.134 13.667 0.000 1.828 1.828
## Cadri32a|t1 0.622 0.075 8.324 0.000 0.622 0.622
## Cadri32a|t2 1.569 0.112 14.040 0.000 1.569 1.569
## Cadri32a|t3 1.828 0.134 13.667 0.000 1.828 1.828
## Cadri8a|t1 1.347 0.098 13.713 0.000 1.347 1.347
## Cadri8a|t2 2.161 0.177 12.220 0.000 2.161 2.161
## Cadri8a|t3 2.740 0.329 8.326 0.000 2.740 2.740
## Cadri25a|t1 1.257 0.094 13.400 0.000 1.257 1.257
## Cadri25a|t2 2.249 0.192 11.707 0.000 2.249 2.249
## Cadri30a|t1 1.257 0.094 13.400 0.000 1.257 1.257
## Cadri30a|t2 2.024 0.157 12.925 0.000 2.024 2.024
## Cadri30a|t3 2.504 0.250 10.011 0.000 2.504 2.504
## Cadri34a|t1 1.328 0.097 13.656 0.000 1.328 1.328
## Cadri34a|t2 2.249 0.192 11.707 0.000 2.249 2.249
## Cadri34a|t3 2.740 0.329 8.326 0.000 2.740 2.740
## Cadri31a|t1 2.161 0.177 12.220 0.000 2.161 2.161
## Cadri31a|t2 2.504 0.250 10.011 0.000 2.504 2.504
## Cadri31a|t3 2.740 0.329 8.326 0.000 2.740 2.740
## Cadri33a|t1 1.871 0.138 13.536 0.000 1.871 1.871
## Cadri33a|t2 2.357 0.214 11.014 0.000 2.357 2.357
## Cadri33a|t3 2.740 0.329 8.326 0.000 2.740 2.740
## Cadri20a|t1 1.717 0.123 13.919 0.000 1.717 1.717
## Cadri20a|t2 2.161 0.177 12.220 0.000 2.161 2.161
## Cadri20a|t3 2.504 0.250 10.011 0.000 2.504 2.504
## Cadri21a|t1 1.089 0.087 12.530 0.000 1.089 1.089
## Cadri21a|t2 1.917 0.143 13.374 0.000 1.917 1.917
## Cadri21a|t3 2.357 0.214 11.014 0.000 2.357 2.357
## Cadri35a|t1 1.347 0.098 13.713 0.000 1.347 1.347
## Cadri35a|t2 2.161 0.177 12.220 0.000 2.161 2.161
## Cadri35a|t3 2.504 0.250 10.011 0.000 2.504 2.504
## Cadri2a|t1 1.386 0.100 13.817 0.000 1.386 1.386
## Cadri2a|t2 1.968 0.149 13.174 0.000 1.968 1.968
## Cadri2a|t3 2.249 0.192 11.707 0.000 2.249 2.249
## Cadri19a|t1 0.558 0.074 7.573 0.000 0.558 0.558
## Cadri19a|t2 1.257 0.094 13.400 0.000 1.257 1.257
## Cadri19a|t3 1.789 0.130 13.772 0.000 1.789 1.789
##
## Variances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .Cadri7a 0.445 0.445 0.445
## .Cadri9a 0.600 0.600 0.600
## .Cadri12a 0.399 0.399 0.399
## .Cadri17a 0.294 0.294 0.294
## .Cadri24a 0.534 0.534 0.534
## .Cadri28a 0.514 0.514 0.514
## .Cadri32a 0.452 0.452 0.452
## .Cadri8a 0.296 0.296 0.296
## .Cadri25a 0.386 0.386 0.386
## .Cadri30a 0.222 0.222 0.222
## .Cadri34a 0.322 0.322 0.322
## .Cadri31a 0.391 0.391 0.391
## .Cadri33a 0.080 0.080 0.080
## .Cadri20a 0.286 0.286 0.286
## .Cadri21a 0.280 0.280 0.280
## .Cadri35a 0.485 0.485 0.485
## .Cadri2a 0.645 0.645 0.645
## .Cadri19a 0.372 0.372 0.372
## V_verbal 0.555 0.052 10.596 0.000 1.000 1.000
## V_fisica 0.704 0.072 9.714 0.000 1.000 1.000
## C_amenaz 0.609 0.114 5.341 0.000 1.000 1.000
## V_relaci 0.714 0.136 5.268 0.000 1.000 1.000
## V_sexual 0.355 0.104 3.421 0.001 1.000 1.000
##
## Scales y*:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## Cadri7a 1.000 1.000 1.000
## Cadri9a 1.000 1.000 1.000
## Cadri12a 1.000 1.000 1.000
## Cadri17a 1.000 1.000 1.000
## Cadri24a 1.000 1.000 1.000
## Cadri28a 1.000 1.000 1.000
## Cadri32a 1.000 1.000 1.000
## Cadri8a 1.000 1.000 1.000
## Cadri25a 1.000 1.000 1.000
## Cadri30a 1.000 1.000 1.000
## Cadri34a 1.000 1.000 1.000
## Cadri31a 1.000 1.000 1.000
## Cadri33a 1.000 1.000 1.000
## Cadri20a 1.000 1.000 1.000
## Cadri21a 1.000 1.000 1.000
## Cadri35a 1.000 1.000 1.000
## Cadri2a 1.000 1.000 1.000
## Cadri19a 1.000 1.000 1.000
## lhs op rhs mi epc sepc.lv sepc.all sepc.nox
## 353 Cadri31a ~~ Cadri35a 10.471 -0.236 -0.236 -0.541 -0.541
## 351 Cadri31a ~~ Cadri20a 10.303 0.324 0.324 0.968 0.968
## 244 Cadri9a ~~ Cadri31a 9.258 0.309 0.309 0.638 0.638
## 189 V_relaci =~ Cadri12a 8.247 -0.492 -0.415 -0.415 -0.415
## 291 Cadri24a ~~ Cadri2a 4.942 -0.189 -0.189 -0.322 -0.322
## 185 C_amenaz =~ Cadri2a 4.651 -1.116 -0.871 -0.871 -0.871
## 186 C_amenaz =~ Cadri19a 4.651 1.483 1.157 1.157 1.157
## 169 V_fisica =~ Cadri2a 4.278 -0.664 -0.557 -0.557 -0.557
## 170 V_fisica =~ Cadri19a 4.278 0.882 0.740 0.740 0.740
## 159 V_fisica =~ Cadri12a 4.183 0.268 0.225 0.225 0.225
## 336 Cadri30a ~~ Cadri31a 3.910 0.193 0.193 0.654 0.654
## 255 Cadri12a ~~ Cadri8a 3.725 0.150 0.150 0.435 0.435
## 368 Cadri35a ~~ Cadri2a 3.609 0.180 0.180 0.322 0.322
## 184 C_amenaz =~ Cadri35a 3.603 -0.277 -0.216 -0.216 -0.216
## 168 V_fisica =~ Cadri35a 3.312 -0.232 -0.195 -0.195 -0.195
## 203 V_sexual =~ Cadri9a 3.232 0.301 0.179 0.179 0.179
## 214 V_sexual =~ Cadri33a 3.013 -0.717 -0.427 -0.427 -0.427
## 213 V_sexual =~ Cadri31a 3.013 0.583 0.348 0.348 0.348
## 223 Cadri7a ~~ Cadri32a 2.643 0.097 0.097 0.216 0.216
## 264 Cadri12a ~~ Cadri2a 2.628 -0.186 -0.186 -0.368 -0.368
## For constructs with categorical indicators, the alpha and the average variance extracted are calculated from polychoric (polyserial) correlations, not from Pearson correlations.
## V_verbal V_fisica C_amenaz V_relaci V_sexual
## alpha 0.8869414 0.9004611 0.8562722 0.8443092 0.6416203
## omega 0.8206988 0.7758095 0.6651273 0.6705323 0.5201420
## omega2 0.8206988 0.7758095 0.6651273 0.6705323 0.5201420
## omega3 0.8260569 0.7763087 0.6651274 0.6695223 0.5201421
## avevar 0.5373876 0.6934556 0.7646412 0.6498375 0.4916250
semPlot::semPaths(fit04_b_fork, whatLabels = "std", label.cex= 1.3,
edge.label.cex = 0.8, nCharEdges = 3,
nCharNodes = 8, sizeLat = 7, sizeLat2 = 4,
sizeMan = 7, sizeMan2 = 2.8, rotation = 2, intercepts = F,
thresholds = F, groups = "latents", pastel = TRUE,
exoVar = FALSE, edge.color = "black",
curvature = 2, mar = c(1, 15, 2, 15), residScale = 10,
manifests = rev(fit04_b_fork@Data@ordered))
title("Modelo Factorial del CADRI \n Modelo 04 con ajustes del modelo 07")Se mantienen los cambios de los modelos 01 al 04 - Sin item 15, 13 (V Sexual) - Sin item 05 (Conducta amenzante) - No considerar al factor Resolución de conflictos como parte del modelo factorial - Sin item 04 y 23 (V. Verbal) - Sin item 03 (V. relacional)
Se adiciona el siguiente cambio: - Unir factor de conducta amenzante con violencia física debido a que el contenido de los ítems hacen alusión a la intención de hacer un daño físico. Esto es mejor a generar errores correlacionados entre ítems que pertenecen a diferentes dimensiones.
model05 <- "# Modelo de medición
V_verbal =~ Cadri7a + Cadri9a + Cadri12a + Cadri17a + Cadri21a +
Cadri24a + Cadri28a + Cadri32a
V_fis_am =~ Cadri8a + Cadri25a + Cadri30a + Cadri34a + Cadri29a + Cadri31a + Cadri33a
V_relaci =~ Cadri20a + Cadri35a
V_sexual =~ Cadri2a + Cadri19a"fit05_a <- cfa(model = model05,
data = cadri_data,
estimator = "MLR")
summary(fit05_a, fit.measures = TRUE, standardized = TRUE)## lavaan 0.6-6 ended normally after 98 iterations
##
## Estimator ML
## Optimization method NLMINB
## Number of free parameters 44
##
## Number of observations 326
##
## Model Test User Model:
## Standard Robust
## Test Statistic 463.603 269.564
## Degrees of freedom 146 146
## P-value (Chi-square) 0.000 0.000
## Scaling correction factor 1.720
## Yuan-Bentler correction (Mplus variant)
##
## Model Test Baseline Model:
##
## Test statistic 1937.884 987.012
## Degrees of freedom 171 171
## P-value 0.000 0.000
## Scaling correction factor 1.963
##
## User Model versus Baseline Model:
##
## Comparative Fit Index (CFI) 0.820 0.849
## Tucker-Lewis Index (TLI) 0.789 0.823
##
## Robust Comparative Fit Index (CFI) 0.867
## Robust Tucker-Lewis Index (TLI) 0.845
##
## Loglikelihood and Information Criteria:
##
## Loglikelihood user model (H0) -3474.738 -3474.738
## Scaling correction factor 6.736
## for the MLR correction
## Loglikelihood unrestricted model (H1) -3242.936 -3242.936
## Scaling correction factor 2.881
## for the MLR correction
##
## Akaike (AIC) 7037.476 7037.476
## Bayesian (BIC) 7204.099 7204.099
## Sample-size adjusted Bayesian (BIC) 7064.534 7064.534
##
## Root Mean Square Error of Approximation:
##
## RMSEA 0.082 0.051
## 90 Percent confidence interval - lower 0.073 0.044
## 90 Percent confidence interval - upper 0.090 0.058
## P-value RMSEA <= 0.05 0.000 0.405
##
## Robust RMSEA 0.067
## 90 Percent confidence interval - lower 0.054
## 90 Percent confidence interval - upper 0.079
##
## Standardized Root Mean Square Residual:
##
## SRMR 0.072 0.072
##
## Parameter Estimates:
##
## Standard errors Sandwich
## Information bread Observed
## Observed information based on Hessian
##
## Latent Variables:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## V_verbal =~
## Cadri7a 1.000 0.540 0.699
## Cadri9a 0.755 0.103 7.315 0.000 0.407 0.530
## Cadri12a 0.888 0.098 9.050 0.000 0.479 0.680
## Cadri17a 0.756 0.084 9.028 0.000 0.408 0.715
## Cadri21a 0.441 0.110 4.024 0.000 0.238 0.489
## Cadri24a 0.636 0.099 6.449 0.000 0.343 0.597
## Cadri28a 0.910 0.098 9.252 0.000 0.491 0.622
## Cadri32a 0.869 0.091 9.543 0.000 0.469 0.676
## V_fis_am =~
## Cadri8a 1.000 0.258 0.693
## Cadri25a 0.766 0.231 3.315 0.001 0.198 0.554
## Cadri30a 1.226 0.289 4.235 0.000 0.317 0.742
## Cadri34a 0.887 0.219 4.059 0.000 0.229 0.629
## Cadri29a 0.374 0.224 1.664 0.096 0.096 0.251
## Cadri31a 0.336 0.214 1.572 0.116 0.087 0.394
## Cadri33a 0.640 0.170 3.758 0.000 0.165 0.617
## V_relaci =~
## Cadri20a 1.000 0.193 0.569
## Cadri35a 1.122 0.436 2.574 0.010 0.217 0.554
## V_sexual =~
## Cadri2a 1.000 0.199 0.442
## Cadri19a 2.257 2.263 0.997 0.319 0.450 0.581
##
## Covariances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## V_verbal ~~
## V_fis_am 0.088 0.031 2.797 0.005 0.629 0.629
## V_relaci 0.076 0.036 2.121 0.034 0.728 0.728
## V_sexual 0.045 0.030 1.501 0.133 0.421 0.421
## V_fis_am ~~
## V_relaci 0.014 0.011 1.351 0.177 0.286 0.286
## V_sexual 0.025 0.014 1.795 0.073 0.486 0.486
## V_relaci ~~
## V_sexual 0.016 0.022 0.728 0.467 0.417 0.417
##
## Variances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .Cadri7a 0.305 0.036 8.481 0.000 0.305 0.511
## .Cadri9a 0.425 0.049 8.604 0.000 0.425 0.719
## .Cadri12a 0.266 0.041 6.415 0.000 0.266 0.537
## .Cadri17a 0.160 0.023 6.811 0.000 0.160 0.489
## .Cadri21a 0.180 0.034 5.258 0.000 0.180 0.761
## .Cadri24a 0.213 0.024 8.875 0.000 0.213 0.644
## .Cadri28a 0.382 0.044 8.705 0.000 0.382 0.613
## .Cadri32a 0.261 0.039 6.789 0.000 0.261 0.543
## .Cadri8a 0.072 0.015 4.770 0.000 0.072 0.519
## .Cadri25a 0.088 0.020 4.440 0.000 0.088 0.693
## .Cadri30a 0.082 0.028 2.888 0.004 0.082 0.449
## .Cadri34a 0.080 0.022 3.579 0.000 0.080 0.604
## .Cadri29a 0.139 0.027 5.149 0.000 0.139 0.937
## .Cadri31a 0.041 0.023 1.760 0.078 0.041 0.845
## .Cadri33a 0.044 0.017 2.690 0.007 0.044 0.619
## .Cadri20a 0.078 0.030 2.642 0.008 0.078 0.676
## .Cadri35a 0.106 0.029 3.656 0.000 0.106 0.693
## .Cadri2a 0.164 0.046 3.543 0.000 0.164 0.805
## .Cadri19a 0.398 0.213 1.870 0.061 0.398 0.663
## V_verbal 0.291 0.059 4.959 0.000 1.000 1.000
## V_fis_am 0.067 0.032 2.091 0.037 1.000 1.000
## V_relaci 0.037 0.025 1.485 0.137 1.000 1.000
## V_sexual 0.040 0.041 0.969 0.332 1.000 1.000
## lhs op rhs mi epc sepc.lv sepc.all sepc.nox
## 76 V_relaci =~ Cadri21a 38.320 1.919 0.371 0.763 0.763
## 243 Cadri30a ~~ Cadri31a 33.673 0.023 0.023 0.391 0.391
## 84 V_relaci =~ Cadri29a 31.307 0.827 0.160 0.415 0.415
## 53 V_verbal =~ Cadri29a 28.624 0.316 0.171 0.443 0.443
## 263 Cadri31a ~~ Cadri20a 20.425 0.016 0.016 0.280 0.280
## 227 Cadri8a ~~ Cadri33a 20.070 0.018 0.018 0.318 0.318
## 74 V_relaci =~ Cadri12a 18.420 -1.713 -0.331 -0.471 -0.471
## 183 Cadri21a ~~ Cadri35a 18.281 0.037 0.037 0.266 0.266
## 182 Cadri21a ~~ Cadri20a 16.910 0.031 0.031 0.258 0.258
## 101 V_sexual =~ Cadri29a 14.912 0.755 0.151 0.391 0.391
## 226 Cadri8a ~~ Cadri31a 14.006 -0.013 -0.013 -0.240 -0.240
## 265 Cadri31a ~~ Cadri2a 13.959 0.018 0.018 0.225 0.225
## 257 Cadri29a ~~ Cadri33a 13.887 -0.018 -0.018 -0.224 -0.224
## 250 Cadri34a ~~ Cadri31a 12.916 -0.013 -0.013 -0.221 -0.221
## 259 Cadri29a ~~ Cadri35a 11.708 0.025 0.025 0.208 0.208
## 166 Cadri17a ~~ Cadri31a 11.197 0.016 0.016 0.203 0.203
## 154 Cadri12a ~~ Cadri35a 10.653 -0.036 -0.036 -0.215 -0.215
## 70 V_fis_am =~ Cadri2a 10.236 -0.926 -0.239 -0.530 -0.530
## 71 V_fis_am =~ Cadri19a 10.236 2.090 0.540 0.697 0.697
## 274 Cadri35a ~~ Cadri2a 10.004 0.029 0.029 0.217 0.217
fit05_b <- cfa(model = model05,
data = cadri_data,
ordered = TRUE,
estimator = "WLSMV",
mimic = "Mplus")## Warning in lav_model_vcov(lavmodel = lavmodel, lavsamplestats = lavsamplestats, : lavaan WARNING:
## The variance-covariance matrix of the estimated parameters (vcov)
## does not appear to be positive definite! The smallest eigenvalue
## (= -5.576008e-17) is smaller than zero. This may be a symptom that
## the model is not identified.
## lavaan 0.6-6 ended normally after 34 iterations
##
## Estimator DWLS
## Optimization method NLMINB
## Number of free parameters 80
##
## Number of observations 326
##
## Model Test User Model:
## Standard Robust
## Test Statistic 180.772 216.053
## Degrees of freedom 146 146
## P-value (Chi-square) 0.027 0.000
## Scaling correction factor 1.241
## Shift parameter 70.420
## simple second-order correction (WLSMV)
##
## Model Test Baseline Model:
##
## Test statistic 6323.983 2674.620
## Degrees of freedom 171 171
## P-value 0.000 0.000
## Scaling correction factor 2.458
##
## User Model versus Baseline Model:
##
## Comparative Fit Index (CFI) 0.994 0.972
## Tucker-Lewis Index (TLI) 0.993 0.967
##
## Robust Comparative Fit Index (CFI) NA
## Robust Tucker-Lewis Index (TLI) NA
##
## Root Mean Square Error of Approximation:
##
## RMSEA 0.027 0.038
## 90 Percent confidence interval - lower 0.010 0.027
## 90 Percent confidence interval - upper 0.039 0.049
## P-value RMSEA <= 0.05 1.000 0.966
##
## Robust RMSEA NA
## 90 Percent confidence interval - lower NA
## 90 Percent confidence interval - upper NA
##
## Standardized Root Mean Square Residual:
##
## SRMR 0.099 0.099
##
## Weighted Root Mean Square Residual:
##
## WRMR 0.894 0.894
##
## Parameter Estimates:
##
## Standard errors Robust.sem
## Information Expected
## Information saturated (h1) model Unstructured
##
## Latent Variables:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## V_verbal =~
## Cadri7a 1.000 0.736 0.736
## Cadri9a 0.866 0.071 12.118 0.000 0.637 0.637
## Cadri12a 1.040 0.066 15.719 0.000 0.765 0.765
## Cadri17a 1.138 0.070 16.357 0.000 0.837 0.837
## Cadri21a 0.916 0.085 10.791 0.000 0.674 0.674
## Cadri24a 0.917 0.062 14.884 0.000 0.675 0.675
## Cadri28a 0.946 0.068 13.968 0.000 0.696 0.696
## Cadri32a 0.999 0.063 15.823 0.000 0.735 0.735
## V_fis_am =~
## Cadri8a 1.000 0.820 0.820
## Cadri25a 0.939 0.075 12.442 0.000 0.770 0.770
## Cadri30a 1.042 0.085 12.245 0.000 0.854 0.854
## Cadri34a 0.977 0.076 12.772 0.000 0.801 0.801
## Cadri29a 0.714 0.090 7.953 0.000 0.586 0.586
## Cadri31a 0.919 0.109 8.418 0.000 0.753 0.753
## Cadri33a 1.142 0.088 13.022 0.000 0.937 0.937
## V_relaci =~
## Cadri20a 1.000 0.837 0.837
## Cadri35a 0.872 0.112 7.807 0.000 0.729 0.729
## V_sexual =~
## Cadri2a 1.000 0.597 0.597
## Cadri19a 1.324 0.294 4.499 0.000 0.791 0.791
##
## Covariances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## V_verbal ~~
## V_fis_am 0.480 0.046 10.350 0.000 0.795 0.795
## V_relaci 0.505 0.069 7.352 0.000 0.820 0.820
## V_sexual 0.201 0.053 3.803 0.000 0.457 0.457
## V_fis_am ~~
## V_relaci 0.360 0.074 4.853 0.000 0.525 0.525
## V_sexual 0.305 0.062 4.933 0.000 0.623 0.623
## V_relaci ~~
## V_sexual 0.277 0.069 4.037 0.000 0.555 0.555
##
## Intercepts:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .Cadri7a 0.000 0.000 0.000
## .Cadri9a 0.000 0.000 0.000
## .Cadri12a 0.000 0.000 0.000
## .Cadri17a 0.000 0.000 0.000
## .Cadri21a 0.000 0.000 0.000
## .Cadri24a 0.000 0.000 0.000
## .Cadri28a 0.000 0.000 0.000
## .Cadri32a 0.000 0.000 0.000
## .Cadri8a 0.000 0.000 0.000
## .Cadri25a 0.000 0.000 0.000
## .Cadri30a 0.000 0.000 0.000
## .Cadri34a 0.000 0.000 0.000
## .Cadri29a 0.000 0.000 0.000
## .Cadri31a 0.000 0.000 0.000
## .Cadri33a 0.000 0.000 0.000
## .Cadri20a 0.000 0.000 0.000
## .Cadri35a 0.000 0.000 0.000
## .Cadri2a 0.000 0.000 0.000
## .Cadri19a 0.000 0.000 0.000
## V_verbal 0.000 0.000 0.000
## V_fis_am 0.000 0.000 0.000
## V_relaci 0.000 0.000 0.000
## V_sexual 0.000 0.000 0.000
##
## Thresholds:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## Cadri7a|t1 0.178 0.070 2.539 0.011 0.178 0.178
## Cadri7a|t2 1.347 0.098 13.713 0.000 1.347 1.347
## Cadri7a|t3 1.717 0.123 13.919 0.000 1.717 1.717
## Cadri9a|t1 0.015 0.070 0.221 0.825 0.015 0.015
## Cadri9a|t2 1.177 0.090 13.029 0.000 1.177 1.177
## Cadri9a|t3 1.871 0.138 13.536 0.000 1.871 1.871
## Cadri12a|t1 0.549 0.074 7.465 0.000 0.549 0.549
## Cadri12a|t2 1.495 0.107 14.000 0.000 1.495 1.495
## Cadri12a|t3 1.871 0.138 13.536 0.000 1.871 1.871
## Cadri17a|t1 0.844 0.079 10.623 0.000 0.844 0.844
## Cadri17a|t2 1.654 0.118 14.003 0.000 1.654 1.654
## Cadri17a|t3 2.357 0.214 11.014 0.000 2.357 2.357
## Cadri21a|t1 1.089 0.087 12.530 0.000 1.089 1.089
## Cadri21a|t2 1.917 0.143 13.374 0.000 1.917 1.917
## Cadri21a|t3 2.357 0.214 11.014 0.000 2.357 2.357
## Cadri24a|t1 0.445 0.072 6.162 0.000 0.445 0.445
## Cadri24a|t2 1.871 0.138 13.536 0.000 1.871 1.871
## Cadri24a|t3 2.357 0.214 11.014 0.000 2.357 2.357
## Cadri28a|t1 0.462 0.072 6.380 0.000 0.462 0.462
## Cadri28a|t2 1.177 0.090 13.029 0.000 1.177 1.177
## Cadri28a|t3 1.828 0.134 13.667 0.000 1.828 1.828
## Cadri32a|t1 0.622 0.075 8.324 0.000 0.622 0.622
## Cadri32a|t2 1.569 0.112 14.040 0.000 1.569 1.569
## Cadri32a|t3 1.828 0.134 13.667 0.000 1.828 1.828
## Cadri8a|t1 1.347 0.098 13.713 0.000 1.347 1.347
## Cadri8a|t2 2.161 0.177 12.220 0.000 2.161 2.161
## Cadri8a|t3 2.740 0.329 8.326 0.000 2.740 2.740
## Cadri25a|t1 1.257 0.094 13.400 0.000 1.257 1.257
## Cadri25a|t2 2.249 0.192 11.707 0.000 2.249 2.249
## Cadri30a|t1 1.257 0.094 13.400 0.000 1.257 1.257
## Cadri30a|t2 2.024 0.157 12.925 0.000 2.024 2.024
## Cadri30a|t3 2.504 0.250 10.011 0.000 2.504 2.504
## Cadri34a|t1 1.328 0.097 13.656 0.000 1.328 1.328
## Cadri34a|t2 2.249 0.192 11.707 0.000 2.249 2.249
## Cadri34a|t3 2.740 0.329 8.326 0.000 2.740 2.740
## Cadri29a|t1 1.292 0.095 13.534 0.000 1.292 1.292
## Cadri29a|t2 2.024 0.157 12.925 0.000 2.024 2.024
## Cadri31a|t1 2.161 0.177 12.220 0.000 2.161 2.161
## Cadri31a|t2 2.504 0.250 10.011 0.000 2.504 2.504
## Cadri31a|t3 2.740 0.329 8.326 0.000 2.740 2.740
## Cadri33a|t1 1.871 0.138 13.536 0.000 1.871 1.871
## Cadri33a|t2 2.357 0.214 11.014 0.000 2.357 2.357
## Cadri33a|t3 2.740 0.329 8.326 0.000 2.740 2.740
## Cadri20a|t1 1.717 0.123 13.919 0.000 1.717 1.717
## Cadri20a|t2 2.161 0.177 12.220 0.000 2.161 2.161
## Cadri20a|t3 2.504 0.250 10.011 0.000 2.504 2.504
## Cadri35a|t1 1.347 0.098 13.713 0.000 1.347 1.347
## Cadri35a|t2 2.161 0.177 12.220 0.000 2.161 2.161
## Cadri35a|t3 2.504 0.250 10.011 0.000 2.504 2.504
## Cadri2a|t1 1.386 0.100 13.817 0.000 1.386 1.386
## Cadri2a|t2 1.968 0.149 13.174 0.000 1.968 1.968
## Cadri2a|t3 2.249 0.192 11.707 0.000 2.249 2.249
## Cadri19a|t1 0.558 0.074 7.573 0.000 0.558 0.558
## Cadri19a|t2 1.257 0.094 13.400 0.000 1.257 1.257
## Cadri19a|t3 1.789 0.130 13.772 0.000 1.789 1.789
##
## Variances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .Cadri7a 0.459 0.459 0.459
## .Cadri9a 0.594 0.594 0.594
## .Cadri12a 0.414 0.414 0.414
## .Cadri17a 0.299 0.299 0.299
## .Cadri21a 0.546 0.546 0.546
## .Cadri24a 0.545 0.545 0.545
## .Cadri28a 0.516 0.516 0.516
## .Cadri32a 0.460 0.460 0.460
## .Cadri8a 0.328 0.328 0.328
## .Cadri25a 0.407 0.407 0.407
## .Cadri30a 0.271 0.271 0.271
## .Cadri34a 0.358 0.358 0.358
## .Cadri29a 0.657 0.657 0.657
## .Cadri31a 0.432 0.432 0.432
## .Cadri33a 0.123 0.123 0.123
## .Cadri20a 0.300 0.300 0.300
## .Cadri35a 0.468 0.468 0.468
## .Cadri2a 0.643 0.643 0.643
## .Cadri19a 0.375 0.375 0.375
## V_verbal 0.541 0.052 10.475 0.000 1.000 1.000
## V_fis_am 0.672 0.075 8.973 0.000 1.000 1.000
## V_relaci 0.700 0.145 4.826 0.000 1.000 1.000
## V_sexual 0.357 0.106 3.369 0.001 1.000 1.000
##
## Scales y*:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## Cadri7a 1.000 1.000 1.000
## Cadri9a 1.000 1.000 1.000
## Cadri12a 1.000 1.000 1.000
## Cadri17a 1.000 1.000 1.000
## Cadri21a 1.000 1.000 1.000
## Cadri24a 1.000 1.000 1.000
## Cadri28a 1.000 1.000 1.000
## Cadri32a 1.000 1.000 1.000
## Cadri8a 1.000 1.000 1.000
## Cadri25a 1.000 1.000 1.000
## Cadri30a 1.000 1.000 1.000
## Cadri34a 1.000 1.000 1.000
## Cadri29a 1.000 1.000 1.000
## Cadri31a 1.000 1.000 1.000
## Cadri33a 1.000 1.000 1.000
## Cadri20a 1.000 1.000 1.000
## Cadri35a 1.000 1.000 1.000
## Cadri2a 1.000 1.000 1.000
## Cadri19a 1.000 1.000 1.000
## lhs op rhs mi epc sepc.lv sepc.all sepc.nox
## 181 V_relaci =~ Cadri29a 34.447 0.841 0.704 0.704 0.704
## 150 V_verbal =~ Cadri29a 28.750 1.121 0.825 0.825 0.825
## 173 V_relaci =~ Cadri21a 18.145 1.004 0.840 0.840 0.840
## 280 Cadri21a ~~ Cadri35a 14.509 0.309 0.309 0.611 0.611
## 360 Cadri31a ~~ Cadri20a 11.464 0.322 0.322 0.893 0.893
## 356 Cadri29a ~~ Cadri35a 11.192 0.354 0.354 0.638 0.638
## 171 V_relaci =~ Cadri12a 9.549 -0.744 -0.622 -0.622 -0.622
## 232 Cadri9a ~~ Cadri31a 8.962 0.300 0.300 0.591 0.591
## 279 Cadri21a ~~ Cadri20a 7.987 0.255 0.255 0.629 0.629
## 353 Cadri29a ~~ Cadri31a 6.750 -0.174 -0.174 -0.327 -0.327
## 231 Cadri9a ~~ Cadri29a 6.495 0.241 0.241 0.385 0.385
## 361 Cadri31a ~~ Cadri35a 5.963 -0.156 -0.156 -0.346 -0.346
## 199 V_sexual =~ Cadri31a 5.508 0.485 0.290 0.290 0.290
## 294 Cadri24a ~~ Cadri2a 4.851 -0.186 -0.186 -0.315 -0.315
## 251 Cadri12a ~~ Cadri35a 4.705 -0.234 -0.234 -0.531 -0.531
## 161 V_fis_am =~ Cadri21a 4.689 -0.407 -0.334 -0.334 -0.334
## 168 V_fis_am =~ Cadri19a 4.628 1.201 0.984 0.984 0.984
## 167 V_fis_am =~ Cadri2a 4.627 -0.907 -0.744 -0.744 -0.744
## 179 V_relaci =~ Cadri30a 4.596 -0.286 -0.239 -0.239 -0.239
## 196 V_sexual =~ Cadri30a 4.138 -0.522 -0.312 -0.312 -0.312
semPlot::semPaths(fit05_b, whatLabels = "std", label.cex= 1.3,
edge.label.cex = 0.8, nCharEdges = 3,
nCharNodes = 8, sizeLat = 7, sizeLat2 = 4,
sizeMan = 7, sizeMan2 = 2.8, rotation = 2, intercepts = F,
thresholds = F, groups = "latents", pastel = TRUE,
exoVar = FALSE, edge.color = "black",
curvature = 2, mar = c(1, 15, 2, 15), residScale = 10,
manifests = rev(fit05_b@Data@ordered))
title("Modelo Factorial del CADRI \n Modelo 05. Conducta amenzante y física juntos")Se mantienen los cambios de los modelos 01 al 04 y 05 - Sin item 15, 13 (V Sexual) - Sin item 05 (Conducta amenzante) - No considerar al factor Resolución de conflictos como parte del modelo factorial - Sin item 04 y 23 (V. Verbal) - Sin item 03 (V. relacional) - Unir factor de conducta amenzante con violencia física
Se adiciona el siguiente cambio: - Ítem 21 pasa a violencia relacional: Su contenido hace referencia directamente a las relaciones de las personas
Nota: Alerta con el ítem 29. Puede tener sesgo por deseabilidad social (el modelo 07 será sin este ítem)
model06 <- "# Modelo de medición
V_verbal =~ Cadri7a + Cadri9a + Cadri12a + Cadri17a + Cadri24a + Cadri28a + Cadri32a
V_fis_am =~ Cadri8a + Cadri25a + Cadri30a + Cadri34a + Cadri29a + Cadri31a + Cadri33a
V_relaci =~ Cadri20a + Cadri21a + Cadri35a
V_sexual =~ Cadri2a + Cadri19a"fit06_a <- cfa(model = model06,
data = cadri_data,
estimator = "MLR")
summary(fit06_a, fit.measures = TRUE, standardized = TRUE)## lavaan 0.6-6 ended normally after 100 iterations
##
## Estimator ML
## Optimization method NLMINB
## Number of free parameters 44
##
## Number of observations 326
##
## Model Test User Model:
## Standard Robust
## Test Statistic 418.887 240.974
## Degrees of freedom 146 146
## P-value (Chi-square) 0.000 0.000
## Scaling correction factor 1.738
## Yuan-Bentler correction (Mplus variant)
##
## Model Test Baseline Model:
##
## Test statistic 1937.884 987.012
## Degrees of freedom 171 171
## P-value 0.000 0.000
## Scaling correction factor 1.963
##
## User Model versus Baseline Model:
##
## Comparative Fit Index (CFI) 0.846 0.884
## Tucker-Lewis Index (TLI) 0.819 0.864
##
## Robust Comparative Fit Index (CFI) 0.897
## Robust Tucker-Lewis Index (TLI) 0.879
##
## Loglikelihood and Information Criteria:
##
## Loglikelihood user model (H0) -3452.379 -3452.379
## Scaling correction factor 6.675
## for the MLR correction
## Loglikelihood unrestricted model (H1) -3242.936 -3242.936
## Scaling correction factor 2.881
## for the MLR correction
##
## Akaike (AIC) 6992.759 6992.759
## Bayesian (BIC) 7159.382 7159.382
## Sample-size adjusted Bayesian (BIC) 7019.817 7019.817
##
## Root Mean Square Error of Approximation:
##
## RMSEA 0.076 0.045
## 90 Percent confidence interval - lower 0.067 0.037
## 90 Percent confidence interval - upper 0.084 0.052
## P-value RMSEA <= 0.05 0.000 0.875
##
## Robust RMSEA 0.059
## 90 Percent confidence interval - lower 0.045
## 90 Percent confidence interval - upper 0.072
##
## Standardized Root Mean Square Residual:
##
## SRMR 0.068 0.068
##
## Parameter Estimates:
##
## Standard errors Sandwich
## Information bread Observed
## Observed information based on Hessian
##
## Latent Variables:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## V_verbal =~
## Cadri7a 1.000 0.541 0.701
## Cadri9a 0.757 0.103 7.356 0.000 0.410 0.533
## Cadri12a 0.898 0.101 8.923 0.000 0.486 0.690
## Cadri17a 0.754 0.085 8.842 0.000 0.408 0.714
## Cadri24a 0.630 0.098 6.423 0.000 0.341 0.593
## Cadri28a 0.913 0.102 8.942 0.000 0.494 0.625
## Cadri32a 0.872 0.092 9.464 0.000 0.472 0.680
## V_fis_am =~
## Cadri8a 1.000 0.258 0.693
## Cadri25a 0.765 0.230 3.331 0.001 0.198 0.553
## Cadri30a 1.228 0.289 4.247 0.000 0.317 0.744
## Cadri34a 0.882 0.216 4.092 0.000 0.228 0.626
## Cadri29a 0.374 0.225 1.663 0.096 0.097 0.251
## Cadri31a 0.339 0.213 1.588 0.112 0.088 0.398
## Cadri33a 0.641 0.168 3.805 0.000 0.166 0.618
## V_relaci =~
## Cadri20a 1.000 0.197 0.581
## Cadri21a 1.752 0.417 4.203 0.000 0.346 0.711
## Cadri35a 1.133 0.397 2.852 0.004 0.224 0.571
## V_sexual =~
## Cadri2a 1.000 0.175 0.389
## Cadri19a 2.914 1.811 1.609 0.108 0.511 0.660
##
## Covariances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## V_verbal ~~
## V_fis_am 0.089 0.031 2.838 0.005 0.636 0.636
## V_relaci 0.070 0.033 2.112 0.035 0.653 0.653
## V_sexual 0.038 0.023 1.681 0.093 0.403 0.403
## V_fis_am ~~
## V_relaci 0.015 0.008 1.878 0.060 0.302 0.302
## V_sexual 0.021 0.011 1.878 0.060 0.467 0.467
## V_relaci ~~
## V_sexual 0.009 0.008 1.165 0.244 0.271 0.271
##
## Variances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .Cadri7a 0.303 0.037 8.092 0.000 0.303 0.509
## .Cadri9a 0.423 0.049 8.600 0.000 0.423 0.716
## .Cadri12a 0.259 0.041 6.307 0.000 0.259 0.523
## .Cadri17a 0.160 0.024 6.719 0.000 0.160 0.490
## .Cadri24a 0.215 0.024 8.892 0.000 0.215 0.649
## .Cadri28a 0.380 0.044 8.608 0.000 0.380 0.609
## .Cadri32a 0.259 0.038 6.806 0.000 0.259 0.538
## .Cadri8a 0.072 0.015 4.777 0.000 0.072 0.519
## .Cadri25a 0.089 0.020 4.457 0.000 0.089 0.694
## .Cadri30a 0.081 0.028 2.894 0.004 0.081 0.447
## .Cadri34a 0.081 0.022 3.612 0.000 0.081 0.608
## .Cadri29a 0.139 0.027 5.157 0.000 0.139 0.937
## .Cadri31a 0.041 0.023 1.760 0.078 0.041 0.842
## .Cadri33a 0.044 0.017 2.681 0.007 0.044 0.618
## .Cadri20a 0.077 0.029 2.649 0.008 0.077 0.663
## .Cadri21a 0.117 0.033 3.520 0.000 0.117 0.494
## .Cadri35a 0.103 0.030 3.423 0.001 0.103 0.674
## .Cadri2a 0.173 0.044 3.968 0.000 0.173 0.849
## .Cadri19a 0.339 0.179 1.901 0.057 0.339 0.565
## V_verbal 0.293 0.060 4.892 0.000 1.000 1.000
## V_fis_am 0.067 0.032 2.095 0.036 1.000 1.000
## V_relaci 0.039 0.026 1.502 0.133 1.000 1.000
## V_sexual 0.031 0.022 1.416 0.157 1.000 1.000
## lhs op rhs mi epc sepc.lv sepc.all sepc.nox
## 234 Cadri30a ~~ Cadri31a 32.839 0.022 0.022 0.387 0.387
## 53 V_verbal =~ Cadri29a 27.602 0.315 0.170 0.442 0.442
## 84 V_relaci =~ Cadri29a 24.482 0.671 0.132 0.344 0.344
## 257 Cadri31a ~~ Cadri20a 23.844 0.017 0.017 0.297 0.297
## 216 Cadri8a ~~ Cadri33a 19.911 0.018 0.018 0.317 0.317
## 260 Cadri31a ~~ Cadri2a 14.837 0.019 0.019 0.227 0.227
## 215 Cadri8a ~~ Cadri31a 14.635 -0.013 -0.013 -0.246 -0.246
## 250 Cadri29a ~~ Cadri33a 13.989 -0.018 -0.018 -0.225 -0.225
## 274 Cadri35a ~~ Cadri2a 13.499 0.031 0.031 0.230 0.230
## 242 Cadri34a ~~ Cadri31a 12.995 -0.013 -0.013 -0.222 -0.222
## 253 Cadri29a ~~ Cadri35a 12.051 0.025 0.025 0.208 0.208
## 165 Cadri17a ~~ Cadri31a 11.998 0.017 0.017 0.211 0.211
## 100 V_sexual =~ Cadri29a 11.467 0.703 0.123 0.320 0.320
## 75 V_relaci =~ Cadri12a 9.976 -0.919 -0.181 -0.258 -0.258
## 163 Cadri17a ~~ Cadri34a 9.711 -0.023 -0.023 -0.199 -0.199
## 150 Cadri12a ~~ Cadri31a 8.447 -0.018 -0.018 -0.175 -0.175
## 133 Cadri9a ~~ Cadri29a 7.849 0.039 0.039 0.161 0.161
## 265 Cadri33a ~~ Cadri2a 7.813 -0.015 -0.015 -0.173 -0.173
## 77 V_relaci =~ Cadri24a 7.231 0.681 0.134 0.234 0.234
## 154 Cadri12a ~~ Cadri35a 7.161 -0.028 -0.028 -0.172 -0.172
fit06_b <- cfa(model = model06,
data = cadri_data,
ordered = TRUE,
estimator = "WLSMV",
mimic = "Mplus")## Warning in lav_model_vcov(lavmodel = lavmodel, lavsamplestats = lavsamplestats, : lavaan WARNING:
## The variance-covariance matrix of the estimated parameters (vcov)
## does not appear to be positive definite! The smallest eigenvalue
## (= -4.365953e-17) is smaller than zero. This may be a symptom that
## the model is not identified.
## lavaan 0.6-6 ended normally after 35 iterations
##
## Estimator DWLS
## Optimization method NLMINB
## Number of free parameters 80
##
## Number of observations 326
##
## Model Test User Model:
## Standard Robust
## Test Statistic 158.470 199.551
## Degrees of freedom 146 146
## P-value (Chi-square) 0.227 0.002
## Scaling correction factor 1.226
## Shift parameter 70.273
## simple second-order correction (WLSMV)
##
## Model Test Baseline Model:
##
## Test statistic 6323.983 2674.620
## Degrees of freedom 171 171
## P-value 0.000 0.000
## Scaling correction factor 2.458
##
## User Model versus Baseline Model:
##
## Comparative Fit Index (CFI) 0.998 0.979
## Tucker-Lewis Index (TLI) 0.998 0.975
##
## Robust Comparative Fit Index (CFI) NA
## Robust Tucker-Lewis Index (TLI) NA
##
## Root Mean Square Error of Approximation:
##
## RMSEA 0.016 0.034
## 90 Percent confidence interval - lower 0.000 0.021
## 90 Percent confidence interval - upper 0.032 0.045
## P-value RMSEA <= 0.05 1.000 0.994
##
## Robust RMSEA NA
## 90 Percent confidence interval - lower NA
## 90 Percent confidence interval - upper NA
##
## Standardized Root Mean Square Residual:
##
## SRMR 0.096 0.096
##
## Weighted Root Mean Square Residual:
##
## WRMR 0.837 0.837
##
## Parameter Estimates:
##
## Standard errors Robust.sem
## Information Expected
## Information saturated (h1) model Unstructured
##
## Latent Variables:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## V_verbal =~
## Cadri7a 1.000 0.741 0.741
## Cadri9a 0.863 0.072 12.064 0.000 0.639 0.639
## Cadri12a 1.040 0.066 15.786 0.000 0.770 0.770
## Cadri17a 1.139 0.070 16.289 0.000 0.843 0.843
## Cadri24a 0.919 0.062 14.847 0.000 0.681 0.681
## Cadri28a 0.947 0.068 13.948 0.000 0.701 0.701
## Cadri32a 0.999 0.063 15.761 0.000 0.740 0.740
## V_fis_am =~
## Cadri8a 1.000 0.820 0.820
## Cadri25a 0.940 0.075 12.449 0.000 0.770 0.770
## Cadri30a 1.042 0.085 12.263 0.000 0.854 0.854
## Cadri34a 0.978 0.077 12.756 0.000 0.802 0.802
## Cadri29a 0.716 0.090 7.974 0.000 0.587 0.587
## Cadri31a 0.916 0.108 8.469 0.000 0.751 0.751
## Cadri33a 1.143 0.088 12.942 0.000 0.937 0.937
## V_relaci =~
## Cadri20a 1.000 0.840 0.840
## Cadri21a 1.002 0.132 7.607 0.000 0.842 0.842
## Cadri35a 0.870 0.107 8.099 0.000 0.731 0.731
## V_sexual =~
## Cadri2a 1.000 0.597 0.597
## Cadri19a 1.326 0.295 4.490 0.000 0.791 0.791
##
## Covariances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## V_verbal ~~
## V_fis_am 0.483 0.047 10.355 0.000 0.795 0.795
## V_relaci 0.455 0.068 6.690 0.000 0.731 0.731
## V_sexual 0.201 0.054 3.765 0.000 0.456 0.456
## V_fis_am ~~
## V_relaci 0.374 0.070 5.376 0.000 0.544 0.544
## V_sexual 0.305 0.062 4.923 0.000 0.623 0.623
## V_relaci ~~
## V_sexual 0.231 0.057 4.045 0.000 0.462 0.462
##
## Intercepts:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .Cadri7a 0.000 0.000 0.000
## .Cadri9a 0.000 0.000 0.000
## .Cadri12a 0.000 0.000 0.000
## .Cadri17a 0.000 0.000 0.000
## .Cadri24a 0.000 0.000 0.000
## .Cadri28a 0.000 0.000 0.000
## .Cadri32a 0.000 0.000 0.000
## .Cadri8a 0.000 0.000 0.000
## .Cadri25a 0.000 0.000 0.000
## .Cadri30a 0.000 0.000 0.000
## .Cadri34a 0.000 0.000 0.000
## .Cadri29a 0.000 0.000 0.000
## .Cadri31a 0.000 0.000 0.000
## .Cadri33a 0.000 0.000 0.000
## .Cadri20a 0.000 0.000 0.000
## .Cadri21a 0.000 0.000 0.000
## .Cadri35a 0.000 0.000 0.000
## .Cadri2a 0.000 0.000 0.000
## .Cadri19a 0.000 0.000 0.000
## V_verbal 0.000 0.000 0.000
## V_fis_am 0.000 0.000 0.000
## V_relaci 0.000 0.000 0.000
## V_sexual 0.000 0.000 0.000
##
## Thresholds:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## Cadri7a|t1 0.178 0.070 2.539 0.011 0.178 0.178
## Cadri7a|t2 1.347 0.098 13.713 0.000 1.347 1.347
## Cadri7a|t3 1.717 0.123 13.919 0.000 1.717 1.717
## Cadri9a|t1 0.015 0.070 0.221 0.825 0.015 0.015
## Cadri9a|t2 1.177 0.090 13.029 0.000 1.177 1.177
## Cadri9a|t3 1.871 0.138 13.536 0.000 1.871 1.871
## Cadri12a|t1 0.549 0.074 7.465 0.000 0.549 0.549
## Cadri12a|t2 1.495 0.107 14.000 0.000 1.495 1.495
## Cadri12a|t3 1.871 0.138 13.536 0.000 1.871 1.871
## Cadri17a|t1 0.844 0.079 10.623 0.000 0.844 0.844
## Cadri17a|t2 1.654 0.118 14.003 0.000 1.654 1.654
## Cadri17a|t3 2.357 0.214 11.014 0.000 2.357 2.357
## Cadri24a|t1 0.445 0.072 6.162 0.000 0.445 0.445
## Cadri24a|t2 1.871 0.138 13.536 0.000 1.871 1.871
## Cadri24a|t3 2.357 0.214 11.014 0.000 2.357 2.357
## Cadri28a|t1 0.462 0.072 6.380 0.000 0.462 0.462
## Cadri28a|t2 1.177 0.090 13.029 0.000 1.177 1.177
## Cadri28a|t3 1.828 0.134 13.667 0.000 1.828 1.828
## Cadri32a|t1 0.622 0.075 8.324 0.000 0.622 0.622
## Cadri32a|t2 1.569 0.112 14.040 0.000 1.569 1.569
## Cadri32a|t3 1.828 0.134 13.667 0.000 1.828 1.828
## Cadri8a|t1 1.347 0.098 13.713 0.000 1.347 1.347
## Cadri8a|t2 2.161 0.177 12.220 0.000 2.161 2.161
## Cadri8a|t3 2.740 0.329 8.326 0.000 2.740 2.740
## Cadri25a|t1 1.257 0.094 13.400 0.000 1.257 1.257
## Cadri25a|t2 2.249 0.192 11.707 0.000 2.249 2.249
## Cadri30a|t1 1.257 0.094 13.400 0.000 1.257 1.257
## Cadri30a|t2 2.024 0.157 12.925 0.000 2.024 2.024
## Cadri30a|t3 2.504 0.250 10.011 0.000 2.504 2.504
## Cadri34a|t1 1.328 0.097 13.656 0.000 1.328 1.328
## Cadri34a|t2 2.249 0.192 11.707 0.000 2.249 2.249
## Cadri34a|t3 2.740 0.329 8.326 0.000 2.740 2.740
## Cadri29a|t1 1.292 0.095 13.534 0.000 1.292 1.292
## Cadri29a|t2 2.024 0.157 12.925 0.000 2.024 2.024
## Cadri31a|t1 2.161 0.177 12.220 0.000 2.161 2.161
## Cadri31a|t2 2.504 0.250 10.011 0.000 2.504 2.504
## Cadri31a|t3 2.740 0.329 8.326 0.000 2.740 2.740
## Cadri33a|t1 1.871 0.138 13.536 0.000 1.871 1.871
## Cadri33a|t2 2.357 0.214 11.014 0.000 2.357 2.357
## Cadri33a|t3 2.740 0.329 8.326 0.000 2.740 2.740
## Cadri20a|t1 1.717 0.123 13.919 0.000 1.717 1.717
## Cadri20a|t2 2.161 0.177 12.220 0.000 2.161 2.161
## Cadri20a|t3 2.504 0.250 10.011 0.000 2.504 2.504
## Cadri21a|t1 1.089 0.087 12.530 0.000 1.089 1.089
## Cadri21a|t2 1.917 0.143 13.374 0.000 1.917 1.917
## Cadri21a|t3 2.357 0.214 11.014 0.000 2.357 2.357
## Cadri35a|t1 1.347 0.098 13.713 0.000 1.347 1.347
## Cadri35a|t2 2.161 0.177 12.220 0.000 2.161 2.161
## Cadri35a|t3 2.504 0.250 10.011 0.000 2.504 2.504
## Cadri2a|t1 1.386 0.100 13.817 0.000 1.386 1.386
## Cadri2a|t2 1.968 0.149 13.174 0.000 1.968 1.968
## Cadri2a|t3 2.249 0.192 11.707 0.000 2.249 2.249
## Cadri19a|t1 0.558 0.074 7.573 0.000 0.558 0.558
## Cadri19a|t2 1.257 0.094 13.400 0.000 1.257 1.257
## Cadri19a|t3 1.789 0.130 13.772 0.000 1.789 1.789
##
## Variances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .Cadri7a 0.451 0.451 0.451
## .Cadri9a 0.592 0.592 0.592
## .Cadri12a 0.407 0.407 0.407
## .Cadri17a 0.289 0.289 0.289
## .Cadri24a 0.537 0.537 0.537
## .Cadri28a 0.508 0.508 0.508
## .Cadri32a 0.452 0.452 0.452
## .Cadri8a 0.328 0.328 0.328
## .Cadri25a 0.407 0.407 0.407
## .Cadri30a 0.270 0.270 0.270
## .Cadri34a 0.358 0.358 0.358
## .Cadri29a 0.656 0.656 0.656
## .Cadri31a 0.436 0.436 0.436
## .Cadri33a 0.122 0.122 0.122
## .Cadri20a 0.294 0.294 0.294
## .Cadri21a 0.291 0.291 0.291
## .Cadri35a 0.466 0.466 0.466
## .Cadri2a 0.644 0.644 0.644
## .Cadri19a 0.374 0.374 0.374
## V_verbal 0.549 0.053 10.436 0.000 1.000 1.000
## V_fis_am 0.672 0.075 8.968 0.000 1.000 1.000
## V_relaci 0.706 0.135 5.217 0.000 1.000 1.000
## V_sexual 0.356 0.106 3.361 0.001 1.000 1.000
##
## Scales y*:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## Cadri7a 1.000 1.000 1.000
## Cadri9a 1.000 1.000 1.000
## Cadri12a 1.000 1.000 1.000
## Cadri17a 1.000 1.000 1.000
## Cadri24a 1.000 1.000 1.000
## Cadri28a 1.000 1.000 1.000
## Cadri32a 1.000 1.000 1.000
## Cadri8a 1.000 1.000 1.000
## Cadri25a 1.000 1.000 1.000
## Cadri30a 1.000 1.000 1.000
## Cadri34a 1.000 1.000 1.000
## Cadri29a 1.000 1.000 1.000
## Cadri31a 1.000 1.000 1.000
## Cadri33a 1.000 1.000 1.000
## Cadri20a 1.000 1.000 1.000
## Cadri21a 1.000 1.000 1.000
## Cadri35a 1.000 1.000 1.000
## Cadri2a 1.000 1.000 1.000
## Cadri19a 1.000 1.000 1.000
## lhs op rhs mi epc sepc.lv sepc.all sepc.nox
## 181 V_relaci =~ Cadri29a 30.118 0.776 0.652 0.652 0.652
## 150 V_verbal =~ Cadri29a 26.244 1.112 0.823 0.823 0.823
## 350 Cadri29a ~~ Cadri35a 10.494 0.341 0.341 0.616 0.616
## 354 Cadri31a ~~ Cadri20a 10.018 0.294 0.294 0.821 0.821
## 231 Cadri9a ~~ Cadri31a 8.973 0.300 0.300 0.591 0.591
## 346 Cadri29a ~~ Cadri31a 6.637 -0.172 -0.172 -0.322 -0.322
## 356 Cadri31a ~~ Cadri35a 6.505 -0.155 -0.155 -0.345 -0.345
## 230 Cadri9a ~~ Cadri29a 6.425 0.240 0.240 0.384 0.384
## 172 V_relaci =~ Cadri12a 6.204 -0.458 -0.384 -0.384 -0.384
## 198 V_sexual =~ Cadri31a 5.396 0.497 0.297 0.297 0.297
## 281 Cadri24a ~~ Cadri2a 4.924 -0.188 -0.188 -0.320 -0.320
## 179 V_relaci =~ Cadri30a 4.733 -0.301 -0.253 -0.253 -0.253
## 195 V_sexual =~ Cadri30a 4.157 -0.533 -0.318 -0.318 -0.318
## 347 Cadri29a ~~ Cadri33a 3.980 -0.422 -0.422 -1.490 -1.490
## 357 Cadri31a ~~ Cadri2a 3.781 0.140 0.140 0.265 0.265
## 331 Cadri30a ~~ Cadri31a 3.750 0.176 0.176 0.512 0.512
## 168 V_fis_am =~ Cadri2a 3.704 -1.077 -0.883 -0.883 -0.883
## 169 V_fis_am =~ Cadri19a 3.704 1.428 1.170 1.170 1.170
## 261 Cadri17a ~~ Cadri29a 3.601 0.174 0.174 0.400 0.400
## 371 Cadri35a ~~ Cadri2a 3.425 0.176 0.176 0.321 0.321
semPlot::semPaths(fit06_b, whatLabels = "std", label.cex= 1.3,
edge.label.cex = 0.8, nCharEdges = 3,
nCharNodes = 8, sizeLat = 7, sizeLat2 = 4,
sizeMan = 7, sizeMan2 = 2.8, rotation = 2, intercepts = F,
thresholds = F, groups = "latents", pastel = TRUE,
exoVar = FALSE, edge.color = "black",
curvature = 2, mar = c(1, 15, 1, 15), residScale = 10,
manifests = rev(fit06_b@Data@ordered))
title("Modelo Factorial del CADRI \n Modelo 06 basado en modelo 05")Se mantienen los cambios de los modelos 01 al 04 y 05 - Sin item 15, 13 (V Sexual) - Sin item 05 (Conducta amenzante) - No considerar al factor Resolución de conflictos como parte del modelo factorial - Sin item 04 y 23 (V. Verbal) - Sin item 03 (V. relacional) - Unir factor de conducta amenzante con violencia física - Ítem 21 pasa a violencia relacional
Se adiciona el siguiente cambio: - Quitar el ítem 29. Presenta carga compuesta
model07 <- "# Modelo de medición
V_verbal =~ Cadri7a + Cadri9a + Cadri12a + Cadri17a + Cadri24a + Cadri28a + Cadri32a
V_fis_am =~ Cadri8a + Cadri25a + Cadri30a + Cadri34a + Cadri31a + Cadri33a
V_relaci =~ Cadri20a + Cadri21a + Cadri35a
V_sexual =~ Cadri2a + Cadri19a"fit07_a <- cfa(model = model07,
data = cadri_data,
estimator = "MLR")
summary(fit07_a, fit.measures = TRUE, standardized = TRUE)## lavaan 0.6-6 ended normally after 105 iterations
##
## Estimator ML
## Optimization method NLMINB
## Number of free parameters 42
##
## Number of observations 326
##
## Model Test User Model:
## Standard Robust
## Test Statistic 342.193 198.818
## Degrees of freedom 129 129
## P-value (Chi-square) 0.000 0.000
## Scaling correction factor 1.721
## Yuan-Bentler correction (Mplus variant)
##
## Model Test Baseline Model:
##
## Test statistic 1844.236 940.536
## Degrees of freedom 153 153
## P-value 0.000 0.000
## Scaling correction factor 1.961
##
## User Model versus Baseline Model:
##
## Comparative Fit Index (CFI) 0.874 0.911
## Tucker-Lewis Index (TLI) 0.850 0.895
##
## Robust Comparative Fit Index (CFI) 0.922
## Robust Tucker-Lewis Index (TLI) 0.908
##
## Loglikelihood and Information Criteria:
##
## Loglikelihood user model (H0) -3309.409 -3309.409
## Scaling correction factor 6.740
## for the MLR correction
## Loglikelihood unrestricted model (H1) -3138.313 -3138.313
## Scaling correction factor 2.954
## for the MLR correction
##
## Akaike (AIC) 6702.819 6702.819
## Bayesian (BIC) 6861.868 6861.868
## Sample-size adjusted Bayesian (BIC) 6728.647 6728.647
##
## Root Mean Square Error of Approximation:
##
## RMSEA 0.071 0.041
## 90 Percent confidence interval - lower 0.062 0.032
## 90 Percent confidence interval - upper 0.080 0.049
## P-value RMSEA <= 0.05 0.000 0.967
##
## Robust RMSEA 0.053
## 90 Percent confidence interval - lower 0.038
## 90 Percent confidence interval - upper 0.068
##
## Standardized Root Mean Square Residual:
##
## SRMR 0.057 0.057
##
## Parameter Estimates:
##
## Standard errors Sandwich
## Information bread Observed
## Observed information based on Hessian
##
## Latent Variables:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## V_verbal =~
## Cadri7a 1.000 0.542 0.702
## Cadri9a 0.755 0.102 7.380 0.000 0.409 0.532
## Cadri12a 0.898 0.100 8.997 0.000 0.486 0.691
## Cadri17a 0.752 0.085 8.844 0.000 0.408 0.714
## Cadri24a 0.629 0.098 6.432 0.000 0.341 0.593
## Cadri28a 0.911 0.102 8.972 0.000 0.493 0.625
## Cadri32a 0.872 0.091 9.538 0.000 0.473 0.681
## V_fis_am =~
## Cadri8a 1.000 0.260 0.697
## Cadri25a 0.752 0.230 3.275 0.001 0.195 0.547
## Cadri30a 1.230 0.283 4.350 0.000 0.319 0.748
## Cadri34a 0.880 0.222 3.959 0.000 0.228 0.627
## Cadri31a 0.334 0.206 1.623 0.105 0.087 0.393
## Cadri33a 0.651 0.163 3.983 0.000 0.169 0.631
## V_relaci =~
## Cadri20a 1.000 0.197 0.581
## Cadri21a 1.751 0.414 4.231 0.000 0.346 0.711
## Cadri35a 1.134 0.398 2.851 0.004 0.224 0.571
## V_sexual =~
## Cadri2a 1.000 0.175 0.387
## Cadri19a 2.943 1.828 1.610 0.108 0.514 0.663
##
## Covariances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## V_verbal ~~
## V_fis_am 0.087 0.031 2.766 0.006 0.618 0.618
## V_relaci 0.070 0.033 2.118 0.034 0.653 0.653
## V_sexual 0.038 0.023 1.682 0.093 0.401 0.401
## V_fis_am ~~
## V_relaci 0.015 0.008 1.728 0.084 0.283 0.283
## V_sexual 0.020 0.011 1.921 0.055 0.449 0.449
## V_relaci ~~
## V_sexual 0.009 0.008 1.160 0.246 0.270 0.270
##
## Variances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .Cadri7a 0.303 0.037 8.098 0.000 0.303 0.508
## .Cadri9a 0.424 0.049 8.606 0.000 0.424 0.717
## .Cadri12a 0.259 0.041 6.312 0.000 0.259 0.523
## .Cadri17a 0.160 0.024 6.669 0.000 0.160 0.491
## .Cadri24a 0.215 0.024 8.875 0.000 0.215 0.649
## .Cadri28a 0.380 0.044 8.610 0.000 0.380 0.610
## .Cadri32a 0.258 0.038 6.830 0.000 0.258 0.536
## .Cadri8a 0.071 0.015 4.888 0.000 0.071 0.515
## .Cadri25a 0.089 0.020 4.494 0.000 0.089 0.701
## .Cadri30a 0.080 0.028 2.826 0.005 0.080 0.440
## .Cadri34a 0.080 0.022 3.639 0.000 0.080 0.607
## .Cadri31a 0.041 0.024 1.725 0.085 0.041 0.845
## .Cadri33a 0.043 0.016 2.711 0.007 0.043 0.602
## .Cadri20a 0.077 0.029 2.649 0.008 0.077 0.663
## .Cadri21a 0.117 0.033 3.526 0.000 0.117 0.495
## .Cadri35a 0.103 0.030 3.426 0.001 0.103 0.674
## .Cadri2a 0.173 0.044 3.945 0.000 0.173 0.850
## .Cadri19a 0.337 0.181 1.858 0.063 0.337 0.561
## V_verbal 0.293 0.060 4.915 0.000 1.000 1.000
## V_fis_am 0.067 0.032 2.098 0.036 1.000 1.000
## V_relaci 0.039 0.026 1.505 0.132 1.000 1.000
## V_sexual 0.030 0.021 1.427 0.154 1.000 1.000
## lhs op rhs mi epc sepc.lv sepc.all sepc.nox
## 219 Cadri30a ~~ Cadri31a 34.324 0.023 0.023 0.398 0.398
## 234 Cadri31a ~~ Cadri20a 23.628 0.017 0.017 0.296 0.296
## 203 Cadri8a ~~ Cadri33a 17.411 0.017 0.017 0.302 0.302
## 237 Cadri31a ~~ Cadri2a 15.246 0.019 0.019 0.230 0.230
## 202 Cadri8a ~~ Cadri31a 14.368 -0.013 -0.013 -0.244 -0.244
## 251 Cadri35a ~~ Cadri2a 13.562 0.031 0.031 0.230 0.230
## 226 Cadri34a ~~ Cadri31a 12.555 -0.013 -0.013 -0.218 -0.218
## 156 Cadri17a ~~ Cadri31a 12.546 0.017 0.017 0.215 0.215
## 72 V_relaci =~ Cadri12a 10.209 -0.929 -0.183 -0.260 -0.260
## 200 Cadri8a ~~ Cadri30a 8.918 -0.019 -0.019 -0.257 -0.257
## 155 Cadri17a ~~ Cadri34a 8.830 -0.022 -0.022 -0.189 -0.189
## 142 Cadri12a ~~ Cadri31a 8.574 -0.018 -0.018 -0.176 -0.176
## 242 Cadri33a ~~ Cadri2a 7.526 -0.015 -0.015 -0.170 -0.170
## 217 Cadri25a ~~ Cadri19a 7.460 0.034 0.034 0.199 0.199
## 180 Cadri28a ~~ Cadri34a 7.424 0.029 0.029 0.168 0.168
## 93 V_sexual =~ Cadri25a 7.306 0.465 0.081 0.228 0.228
## 74 V_relaci =~ Cadri24a 7.200 0.679 0.134 0.233 0.233
## 127 Cadri9a ~~ Cadri31a 7.182 0.020 0.020 0.155 0.155
## 146 Cadri12a ~~ Cadri35a 7.058 -0.028 -0.028 -0.171 -0.171
## 161 Cadri17a ~~ Cadri2a 6.626 0.027 0.027 0.161 0.161
fit07_b <- cfa(model = model07,
data = cadri_data,
ordered = TRUE,
estimator = "WLSMV",
mimic = "Mplus")## Warning in lav_model_vcov(lavmodel = lavmodel, lavsamplestats = lavsamplestats, : lavaan WARNING:
## The variance-covariance matrix of the estimated parameters (vcov)
## does not appear to be positive definite! The smallest eigenvalue
## (= -5.186196e-17) is smaller than zero. This may be a symptom that
## the model is not identified.
## lavaan 0.6-6 ended normally after 32 iterations
##
## Estimator DWLS
## Optimization method NLMINB
## Number of free parameters 77
##
## Number of observations 326
##
## Model Test User Model:
## Standard Robust
## Test Statistic 112.321 157.799
## Degrees of freedom 129 129
## P-value (Chi-square) 0.852 0.043
## Scaling correction factor 1.139
## Shift parameter 59.196
## simple second-order correction (WLSMV)
##
## Model Test Baseline Model:
##
## Test statistic 6023.208 2620.833
## Degrees of freedom 153 153
## P-value 0.000 0.000
## Scaling correction factor 2.379
##
## User Model versus Baseline Model:
##
## Comparative Fit Index (CFI) 1.000 0.988
## Tucker-Lewis Index (TLI) 1.003 0.986
##
## Robust Comparative Fit Index (CFI) NA
## Robust Tucker-Lewis Index (TLI) NA
##
## Root Mean Square Error of Approximation:
##
## RMSEA 0.000 0.026
## 90 Percent confidence interval - lower 0.000 0.005
## 90 Percent confidence interval - upper 0.016 0.039
## P-value RMSEA <= 0.05 1.000 0.999
##
## Robust RMSEA NA
## 90 Percent confidence interval - lower NA
## 90 Percent confidence interval - upper NA
##
## Standardized Root Mean Square Residual:
##
## SRMR 0.082 0.082
##
## Weighted Root Mean Square Residual:
##
## WRMR 0.738 0.738
##
## Parameter Estimates:
##
## Standard errors Robust.sem
## Information Expected
## Information saturated (h1) model Unstructured
##
## Latent Variables:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## V_verbal =~
## Cadri7a 1.000 0.745 0.745
## Cadri9a 0.849 0.071 11.962 0.000 0.632 0.632
## Cadri12a 1.040 0.065 16.093 0.000 0.775 0.775
## Cadri17a 1.128 0.069 16.414 0.000 0.840 0.840
## Cadri24a 0.917 0.061 15.010 0.000 0.683 0.683
## Cadri28a 0.936 0.067 13.895 0.000 0.697 0.697
## Cadri32a 0.995 0.062 16.074 0.000 0.741 0.741
## V_fis_am =~
## Cadri8a 1.000 0.829 0.829
## Cadri25a 0.935 0.073 12.808 0.000 0.775 0.775
## Cadri30a 1.046 0.082 12.726 0.000 0.867 0.867
## Cadri34a 0.980 0.075 13.032 0.000 0.813 0.813
## Cadri31a 0.952 0.113 8.420 0.000 0.790 0.790
## Cadri33a 1.130 0.086 13.147 0.000 0.937 0.937
## V_relaci =~
## Cadri20a 1.000 0.843 0.843
## Cadri21a 1.002 0.131 7.664 0.000 0.845 0.845
## Cadri35a 0.860 0.108 7.988 0.000 0.725 0.725
## V_sexual =~
## Cadri2a 1.000 0.593 0.593
## Cadri19a 1.344 0.296 4.545 0.000 0.797 0.797
##
## Covariances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## V_verbal ~~
## V_fis_am 0.474 0.046 10.191 0.000 0.767 0.767
## V_relaci 0.459 0.068 6.737 0.000 0.731 0.731
## V_sexual 0.200 0.053 3.790 0.000 0.454 0.454
## V_fis_am ~~
## V_relaci 0.343 0.071 4.802 0.000 0.491 0.491
## V_sexual 0.296 0.059 5.047 0.000 0.602 0.602
## V_relaci ~~
## V_sexual 0.230 0.056 4.086 0.000 0.460 0.460
##
## Intercepts:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .Cadri7a 0.000 0.000 0.000
## .Cadri9a 0.000 0.000 0.000
## .Cadri12a 0.000 0.000 0.000
## .Cadri17a 0.000 0.000 0.000
## .Cadri24a 0.000 0.000 0.000
## .Cadri28a 0.000 0.000 0.000
## .Cadri32a 0.000 0.000 0.000
## .Cadri8a 0.000 0.000 0.000
## .Cadri25a 0.000 0.000 0.000
## .Cadri30a 0.000 0.000 0.000
## .Cadri34a 0.000 0.000 0.000
## .Cadri31a 0.000 0.000 0.000
## .Cadri33a 0.000 0.000 0.000
## .Cadri20a 0.000 0.000 0.000
## .Cadri21a 0.000 0.000 0.000
## .Cadri35a 0.000 0.000 0.000
## .Cadri2a 0.000 0.000 0.000
## .Cadri19a 0.000 0.000 0.000
## V_verbal 0.000 0.000 0.000
## V_fis_am 0.000 0.000 0.000
## V_relaci 0.000 0.000 0.000
## V_sexual 0.000 0.000 0.000
##
## Thresholds:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## Cadri7a|t1 0.178 0.070 2.539 0.011 0.178 0.178
## Cadri7a|t2 1.347 0.098 13.713 0.000 1.347 1.347
## Cadri7a|t3 1.717 0.123 13.919 0.000 1.717 1.717
## Cadri9a|t1 0.015 0.070 0.221 0.825 0.015 0.015
## Cadri9a|t2 1.177 0.090 13.029 0.000 1.177 1.177
## Cadri9a|t3 1.871 0.138 13.536 0.000 1.871 1.871
## Cadri12a|t1 0.549 0.074 7.465 0.000 0.549 0.549
## Cadri12a|t2 1.495 0.107 14.000 0.000 1.495 1.495
## Cadri12a|t3 1.871 0.138 13.536 0.000 1.871 1.871
## Cadri17a|t1 0.844 0.079 10.623 0.000 0.844 0.844
## Cadri17a|t2 1.654 0.118 14.003 0.000 1.654 1.654
## Cadri17a|t3 2.357 0.214 11.014 0.000 2.357 2.357
## Cadri24a|t1 0.445 0.072 6.162 0.000 0.445 0.445
## Cadri24a|t2 1.871 0.138 13.536 0.000 1.871 1.871
## Cadri24a|t3 2.357 0.214 11.014 0.000 2.357 2.357
## Cadri28a|t1 0.462 0.072 6.380 0.000 0.462 0.462
## Cadri28a|t2 1.177 0.090 13.029 0.000 1.177 1.177
## Cadri28a|t3 1.828 0.134 13.667 0.000 1.828 1.828
## Cadri32a|t1 0.622 0.075 8.324 0.000 0.622 0.622
## Cadri32a|t2 1.569 0.112 14.040 0.000 1.569 1.569
## Cadri32a|t3 1.828 0.134 13.667 0.000 1.828 1.828
## Cadri8a|t1 1.347 0.098 13.713 0.000 1.347 1.347
## Cadri8a|t2 2.161 0.177 12.220 0.000 2.161 2.161
## Cadri8a|t3 2.740 0.329 8.326 0.000 2.740 2.740
## Cadri25a|t1 1.257 0.094 13.400 0.000 1.257 1.257
## Cadri25a|t2 2.249 0.192 11.707 0.000 2.249 2.249
## Cadri30a|t1 1.257 0.094 13.400 0.000 1.257 1.257
## Cadri30a|t2 2.024 0.157 12.925 0.000 2.024 2.024
## Cadri30a|t3 2.504 0.250 10.011 0.000 2.504 2.504
## Cadri34a|t1 1.328 0.097 13.656 0.000 1.328 1.328
## Cadri34a|t2 2.249 0.192 11.707 0.000 2.249 2.249
## Cadri34a|t3 2.740 0.329 8.326 0.000 2.740 2.740
## Cadri31a|t1 2.161 0.177 12.220 0.000 2.161 2.161
## Cadri31a|t2 2.504 0.250 10.011 0.000 2.504 2.504
## Cadri31a|t3 2.740 0.329 8.326 0.000 2.740 2.740
## Cadri33a|t1 1.871 0.138 13.536 0.000 1.871 1.871
## Cadri33a|t2 2.357 0.214 11.014 0.000 2.357 2.357
## Cadri33a|t3 2.740 0.329 8.326 0.000 2.740 2.740
## Cadri20a|t1 1.717 0.123 13.919 0.000 1.717 1.717
## Cadri20a|t2 2.161 0.177 12.220 0.000 2.161 2.161
## Cadri20a|t3 2.504 0.250 10.011 0.000 2.504 2.504
## Cadri21a|t1 1.089 0.087 12.530 0.000 1.089 1.089
## Cadri21a|t2 1.917 0.143 13.374 0.000 1.917 1.917
## Cadri21a|t3 2.357 0.214 11.014 0.000 2.357 2.357
## Cadri35a|t1 1.347 0.098 13.713 0.000 1.347 1.347
## Cadri35a|t2 2.161 0.177 12.220 0.000 2.161 2.161
## Cadri35a|t3 2.504 0.250 10.011 0.000 2.504 2.504
## Cadri2a|t1 1.386 0.100 13.817 0.000 1.386 1.386
## Cadri2a|t2 1.968 0.149 13.174 0.000 1.968 1.968
## Cadri2a|t3 2.249 0.192 11.707 0.000 2.249 2.249
## Cadri19a|t1 0.558 0.074 7.573 0.000 0.558 0.558
## Cadri19a|t2 1.257 0.094 13.400 0.000 1.257 1.257
## Cadri19a|t3 1.789 0.130 13.772 0.000 1.789 1.789
##
## Variances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .Cadri7a 0.445 0.445 0.445
## .Cadri9a 0.600 0.600 0.600
## .Cadri12a 0.400 0.400 0.400
## .Cadri17a 0.294 0.294 0.294
## .Cadri24a 0.534 0.534 0.534
## .Cadri28a 0.514 0.514 0.514
## .Cadri32a 0.451 0.451 0.451
## .Cadri8a 0.312 0.312 0.312
## .Cadri25a 0.399 0.399 0.399
## .Cadri30a 0.248 0.248 0.248
## .Cadri34a 0.340 0.340 0.340
## .Cadri31a 0.376 0.376 0.376
## .Cadri33a 0.122 0.122 0.122
## .Cadri20a 0.290 0.290 0.290
## .Cadri21a 0.287 0.287 0.287
## .Cadri35a 0.475 0.475 0.475
## .Cadri2a 0.649 0.649 0.649
## .Cadri19a 0.365 0.365 0.365
## V_verbal 0.555 0.052 10.596 0.000 1.000 1.000
## V_fis_am 0.688 0.074 9.275 0.000 1.000 1.000
## V_relaci 0.710 0.135 5.244 0.000 1.000 1.000
## V_sexual 0.351 0.104 3.377 0.001 1.000 1.000
##
## Scales y*:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## Cadri7a 1.000 1.000 1.000
## Cadri9a 1.000 1.000 1.000
## Cadri12a 1.000 1.000 1.000
## Cadri17a 1.000 1.000 1.000
## Cadri24a 1.000 1.000 1.000
## Cadri28a 1.000 1.000 1.000
## Cadri32a 1.000 1.000 1.000
## Cadri8a 1.000 1.000 1.000
## Cadri25a 1.000 1.000 1.000
## Cadri30a 1.000 1.000 1.000
## Cadri34a 1.000 1.000 1.000
## Cadri31a 1.000 1.000 1.000
## Cadri33a 1.000 1.000 1.000
## Cadri20a 1.000 1.000 1.000
## Cadri21a 1.000 1.000 1.000
## Cadri35a 1.000 1.000 1.000
## Cadri2a 1.000 1.000 1.000
## Cadri19a 1.000 1.000 1.000
## lhs op rhs mi epc sepc.lv sepc.all sepc.nox
## 327 Cadri31a ~~ Cadri20a 11.424 0.316 0.316 0.956 0.956
## 220 Cadri9a ~~ Cadri31a 8.898 0.299 0.299 0.630 0.630
## 165 V_relaci =~ Cadri12a 7.244 -0.475 -0.400 -0.400 -0.400
## 189 V_sexual =~ Cadri31a 5.742 0.510 0.302 0.302 0.302
## 267 Cadri24a ~~ Cadri2a 4.858 -0.187 -0.187 -0.318 -0.318
## 329 Cadri31a ~~ Cadri35a 4.785 -0.134 -0.134 -0.318 -0.318
## 187 V_sexual =~ Cadri30a 3.903 -0.507 -0.300 -0.300 -0.300
## 330 Cadri31a ~~ Cadri2a 3.695 0.141 0.141 0.285 0.285
## 344 Cadri35a ~~ Cadri2a 3.597 0.180 0.180 0.324 0.324
## 231 Cadri12a ~~ Cadri8a 3.549 0.145 0.145 0.410 0.410
## 295 Cadri8a ~~ Cadri31a 3.505 -0.227 -0.227 -0.663 -0.663
## 160 V_fis_am =~ Cadri35a 3.495 -0.237 -0.197 -0.197 -0.197
## 161 V_fis_am =~ Cadri2a 3.446 -0.883 -0.732 -0.732 -0.732
## 162 V_fis_am =~ Cadri19a 3.445 1.186 0.984 0.984 0.984
## 153 V_fis_am =~ Cadri12a 2.954 0.231 0.191 0.191 0.191
## 304 Cadri25a ~~ Cadri31a 2.797 -0.189 -0.189 -0.489 -0.489
## 239 Cadri12a ~~ Cadri35a 2.759 -0.178 -0.178 -0.408 -0.408
## 317 Cadri30a ~~ Cadri2a 2.660 -0.141 -0.141 -0.352 -0.352
## 199 Cadri7a ~~ Cadri32a 2.623 0.097 0.097 0.215 0.215
## 240 Cadri12a ~~ Cadri2a 2.578 -0.185 -0.185 -0.363 -0.363
## For constructs with categorical indicators, the alpha and the average variance extracted are calculated from polychoric (polyserial) correlations, not from Pearson correlations.
## V_verbal V_fis_am V_relaci V_sexual
## alpha 0.8869414 0.9257101 0.8443092 0.6416203
## omega 0.8206993 0.8162186 0.6694553 0.5237891
## omega2 0.8206993 0.8162186 0.6694553 0.5237891
## omega3 0.8260642 0.8205415 0.6686990 0.5237894
## avevar 0.5373890 0.7006245 0.6496149 0.4931354
semPlot::semPaths(fit07_b, whatLabels = "std", label.cex= 1.3,
edge.label.cex = 0.8, nCharEdges = 3,
nCharNodes = 8, sizeLat = 8, sizeLat2 = 4,
sizeMan = 7, sizeMan2 = 2.8, rotation = 2, intercepts = F,
thresholds = F, groups = "latents", pastel = TRUE,
exoVar = FALSE, edge.color = "black",
curvature = 2, mar = c(1, 15, 1, 15), residScale = 10,
manifests = rev(fit07_b@Data@ordered))
title("Modelo Factorial del CADRI \n Modelo 07 basado en modelo 05")Este modelo de segundo orden está basado en el Modelo 04 Fork que incluye los cambios encontrados en el modelo 07 con respecto a los ítems, pero considerando al factor de conducta amenzante.
model08 <- "# Modelo de medición
V_verbal =~ Cadri7a + Cadri9a + Cadri12a + Cadri17a +
Cadri24a + Cadri28a + Cadri32a
V_fisica =~ Cadri8a + Cadri25a + Cadri30a + Cadri34a
C_amenaz =~ Cadri31a + Cadri33a
V_relaci =~ Cadri20a + Cadri21a + Cadri35a
V_sexual =~ Cadri2a + Cadri19a
# Segundo orden
Violencia =~ V_fisica + V_verbal + C_amenaz + V_relaci + V_sexual"fit08_a <- cfa(model = model08,
data = cadri_data,
estimator = "MLR")
summary(fit08_a, fit.measures = TRUE, standardized = TRUE)## lavaan 0.6-6 ended normally after 105 iterations
##
## Estimator ML
## Optimization method NLMINB
## Number of free parameters 41
##
## Number of observations 326
##
## Model Test User Model:
## Standard Robust
## Test Statistic 403.491 249.682
## Degrees of freedom 130 130
## P-value (Chi-square) 0.000 0.000
## Scaling correction factor 1.616
## Yuan-Bentler correction (Mplus variant)
##
## Model Test Baseline Model:
##
## Test statistic 1844.236 940.536
## Degrees of freedom 153 153
## P-value 0.000 0.000
## Scaling correction factor 1.961
##
## User Model versus Baseline Model:
##
## Comparative Fit Index (CFI) 0.838 0.848
## Tucker-Lewis Index (TLI) 0.810 0.821
##
## Robust Comparative Fit Index (CFI) 0.875
## Robust Tucker-Lewis Index (TLI) 0.853
##
## Loglikelihood and Information Criteria:
##
## Loglikelihood user model (H0) -3340.058 -3340.058
## Scaling correction factor 7.195
## for the MLR correction
## Loglikelihood unrestricted model (H1) -3138.313 -3138.313
## Scaling correction factor 2.954
## for the MLR correction
##
## Akaike (AIC) 6762.117 6762.117
## Bayesian (BIC) 6917.379 6917.379
## Sample-size adjusted Bayesian (BIC) 6787.330 6787.330
##
## Root Mean Square Error of Approximation:
##
## RMSEA 0.080 0.053
## 90 Percent confidence interval - lower 0.072 0.045
## 90 Percent confidence interval - upper 0.089 0.061
## P-value RMSEA <= 0.05 0.000 0.248
##
## Robust RMSEA 0.068
## 90 Percent confidence interval - lower 0.055
## 90 Percent confidence interval - upper 0.080
##
## Standardized Root Mean Square Residual:
##
## SRMR 0.077 0.077
##
## Parameter Estimates:
##
## Standard errors Sandwich
## Information bread Observed
## Observed information based on Hessian
##
## Latent Variables:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## V_verbal =~
## Cadri7a 1.000 0.541 0.701
## Cadri9a 0.753 0.103 7.295 0.000 0.408 0.530
## Cadri12a 0.919 0.105 8.734 0.000 0.498 0.707
## Cadri17a 0.744 0.088 8.469 0.000 0.403 0.706
## Cadri24a 0.616 0.096 6.399 0.000 0.334 0.580
## Cadri28a 0.914 0.109 8.419 0.000 0.495 0.627
## Cadri32a 0.874 0.093 9.364 0.000 0.473 0.682
## V_fisica =~
## Cadri8a 1.000 0.259 0.696
## Cadri25a 0.786 0.243 3.236 0.001 0.204 0.571
## Cadri30a 1.190 0.255 4.674 0.000 0.308 0.723
## Cadri34a 0.892 0.229 3.888 0.000 0.231 0.635
## C_amenaz =~
## Cadri31a 1.000 0.094 0.425
## Cadri33a 1.980 1.165 1.699 0.089 0.185 0.692
## V_relaci =~
## Cadri20a 1.000 0.193 0.566
## Cadri21a 1.858 0.549 3.385 0.001 0.358 0.736
## Cadri35a 1.138 0.387 2.936 0.003 0.219 0.559
## V_sexual =~
## Cadri2a 1.000 0.168 0.372
## Cadri19a 3.183 1.889 1.685 0.092 0.534 0.689
## Violencia =~
## V_fisica 1.000 0.917 0.917
## V_verbal 1.621 0.607 2.669 0.008 0.711 0.711
## C_amenaz 0.356 0.220 1.621 0.105 0.904 0.904
## V_relaci 0.369 0.231 1.600 0.110 0.455 0.455
## V_sexual 0.341 0.276 1.237 0.216 0.483 0.483
##
## Variances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .Cadri7a 0.303 0.041 7.412 0.000 0.303 0.508
## .Cadri9a 0.425 0.050 8.583 0.000 0.425 0.719
## .Cadri12a 0.248 0.041 6.086 0.000 0.248 0.500
## .Cadri17a 0.164 0.025 6.484 0.000 0.164 0.502
## .Cadri24a 0.219 0.024 9.018 0.000 0.219 0.663
## .Cadri28a 0.379 0.045 8.362 0.000 0.379 0.607
## .Cadri32a 0.258 0.037 6.943 0.000 0.258 0.535
## .Cadri8a 0.072 0.015 4.888 0.000 0.072 0.516
## .Cadri25a 0.086 0.021 4.178 0.000 0.086 0.674
## .Cadri30a 0.087 0.030 2.893 0.004 0.087 0.477
## .Cadri34a 0.079 0.023 3.506 0.000 0.079 0.597
## .Cadri31a 0.040 0.025 1.599 0.110 0.040 0.819
## .Cadri33a 0.037 0.024 1.562 0.118 0.037 0.521
## .Cadri20a 0.078 0.031 2.520 0.012 0.078 0.679
## .Cadri21a 0.108 0.039 2.802 0.005 0.108 0.459
## .Cadri35a 0.105 0.033 3.167 0.002 0.105 0.687
## .Cadri2a 0.175 0.044 3.986 0.000 0.175 0.861
## .Cadri19a 0.315 0.184 1.717 0.086 0.315 0.525
## .V_verbal 0.145 0.056 2.596 0.009 0.494 0.494
## .V_fisica 0.011 0.012 0.911 0.362 0.160 0.160
## .C_amenaz 0.002 0.004 0.369 0.712 0.184 0.184
## .V_relaci 0.029 0.020 1.444 0.149 0.793 0.793
## .V_sexual 0.022 0.014 1.509 0.131 0.767 0.767
## Violencia 0.056 0.034 1.637 0.102 1.000 1.000
fit08_b <- cfa(model = model08,
data = cadri_data,
ordered = TRUE,
estimator = "WLSMV",
mimic = "Mplus")## Warning in lav_model_vcov(lavmodel = lavmodel, lavsamplestats = lavsamplestats, : lavaan WARNING:
## The variance-covariance matrix of the estimated parameters (vcov)
## does not appear to be positive definite! The smallest eigenvalue
## (= -5.666205e-17) is smaller than zero. This may be a symptom that
## the model is not identified.
## lavaan 0.6-6 ended normally after 32 iterations
##
## Estimator DWLS
## Optimization method NLMINB
## Number of free parameters 76
##
## Number of observations 326
##
## Model Test User Model:
## Standard Robust
## Test Statistic 147.253 185.018
## Degrees of freedom 130 130
## P-value (Chi-square) 0.143 0.001
## Scaling correction factor 1.177
## Shift parameter 59.913
## simple second-order correction (WLSMV)
##
## Model Test Baseline Model:
##
## Test statistic 6023.208 2620.833
## Degrees of freedom 153 153
## P-value 0.000 0.000
## Scaling correction factor 2.379
##
## User Model versus Baseline Model:
##
## Comparative Fit Index (CFI) 0.997 0.978
## Tucker-Lewis Index (TLI) 0.997 0.974
##
## Robust Comparative Fit Index (CFI) NA
## Robust Tucker-Lewis Index (TLI) NA
##
## Root Mean Square Error of Approximation:
##
## RMSEA 0.020 0.036
## 90 Percent confidence interval - lower 0.000 0.023
## 90 Percent confidence interval - upper 0.035 0.047
## P-value RMSEA <= 0.05 1.000 0.980
##
## Robust RMSEA NA
## 90 Percent confidence interval - lower NA
## 90 Percent confidence interval - upper NA
##
## Standardized Root Mean Square Residual:
##
## SRMR 0.094 0.094
##
## Weighted Root Mean Square Residual:
##
## WRMR 0.845 0.845
##
## Parameter Estimates:
##
## Standard errors Robust.sem
## Information Expected
## Information saturated (h1) model Unstructured
##
## Latent Variables:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## V_verbal =~
## Cadri7a 1.000 0.745 0.745
## Cadri9a 0.848 0.071 11.964 0.000 0.632 0.632
## Cadri12a 1.036 0.064 16.094 0.000 0.772 0.772
## Cadri17a 1.129 0.070 16.174 0.000 0.841 0.841
## Cadri24a 0.918 0.061 14.991 0.000 0.684 0.684
## Cadri28a 0.940 0.068 13.757 0.000 0.700 0.700
## Cadri32a 0.993 0.062 15.968 0.000 0.740 0.740
## V_fisica =~
## Cadri8a 1.000 0.839 0.839
## Cadri25a 0.934 0.074 12.618 0.000 0.784 0.784
## Cadri30a 1.052 0.085 12.332 0.000 0.882 0.882
## Cadri34a 0.982 0.076 12.949 0.000 0.823 0.823
## C_amenaz =~
## Cadri31a 1.000 0.750 0.750
## Cadri33a 1.331 0.169 7.876 0.000 0.998 0.998
## V_relaci =~
## Cadri20a 1.000 0.853 0.853
## Cadri21a 1.018 0.140 7.268 0.000 0.868 0.868
## Cadri35a 0.806 0.104 7.722 0.000 0.687 0.687
## V_sexual =~
## Cadri2a 1.000 0.596 0.596
## Cadri19a 1.331 0.301 4.420 0.000 0.793 0.793
## Violencia =~
## V_fisica 1.000 0.874 0.874
## V_verbal 0.887 0.101 8.822 0.000 0.872 0.872
## C_amenaz 0.999 0.139 7.200 0.000 0.976 0.976
## V_relaci 0.836 0.133 6.283 0.000 0.719 0.719
## V_sexual 0.483 0.104 4.637 0.000 0.594 0.594
##
## Intercepts:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .Cadri7a 0.000 0.000 0.000
## .Cadri9a 0.000 0.000 0.000
## .Cadri12a 0.000 0.000 0.000
## .Cadri17a 0.000 0.000 0.000
## .Cadri24a 0.000 0.000 0.000
## .Cadri28a 0.000 0.000 0.000
## .Cadri32a 0.000 0.000 0.000
## .Cadri8a 0.000 0.000 0.000
## .Cadri25a 0.000 0.000 0.000
## .Cadri30a 0.000 0.000 0.000
## .Cadri34a 0.000 0.000 0.000
## .Cadri31a 0.000 0.000 0.000
## .Cadri33a 0.000 0.000 0.000
## .Cadri20a 0.000 0.000 0.000
## .Cadri21a 0.000 0.000 0.000
## .Cadri35a 0.000 0.000 0.000
## .Cadri2a 0.000 0.000 0.000
## .Cadri19a 0.000 0.000 0.000
## .V_verbal 0.000 0.000 0.000
## .V_fisica 0.000 0.000 0.000
## .C_amenaz 0.000 0.000 0.000
## .V_relaci 0.000 0.000 0.000
## .V_sexual 0.000 0.000 0.000
## Violencia 0.000 0.000 0.000
##
## Thresholds:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## Cadri7a|t1 0.178 0.070 2.539 0.011 0.178 0.178
## Cadri7a|t2 1.347 0.098 13.713 0.000 1.347 1.347
## Cadri7a|t3 1.717 0.123 13.919 0.000 1.717 1.717
## Cadri9a|t1 0.015 0.070 0.221 0.825 0.015 0.015
## Cadri9a|t2 1.177 0.090 13.029 0.000 1.177 1.177
## Cadri9a|t3 1.871 0.138 13.536 0.000 1.871 1.871
## Cadri12a|t1 0.549 0.074 7.465 0.000 0.549 0.549
## Cadri12a|t2 1.495 0.107 14.000 0.000 1.495 1.495
## Cadri12a|t3 1.871 0.138 13.536 0.000 1.871 1.871
## Cadri17a|t1 0.844 0.079 10.623 0.000 0.844 0.844
## Cadri17a|t2 1.654 0.118 14.003 0.000 1.654 1.654
## Cadri17a|t3 2.357 0.214 11.014 0.000 2.357 2.357
## Cadri24a|t1 0.445 0.072 6.162 0.000 0.445 0.445
## Cadri24a|t2 1.871 0.138 13.536 0.000 1.871 1.871
## Cadri24a|t3 2.357 0.214 11.014 0.000 2.357 2.357
## Cadri28a|t1 0.462 0.072 6.380 0.000 0.462 0.462
## Cadri28a|t2 1.177 0.090 13.029 0.000 1.177 1.177
## Cadri28a|t3 1.828 0.134 13.667 0.000 1.828 1.828
## Cadri32a|t1 0.622 0.075 8.324 0.000 0.622 0.622
## Cadri32a|t2 1.569 0.112 14.040 0.000 1.569 1.569
## Cadri32a|t3 1.828 0.134 13.667 0.000 1.828 1.828
## Cadri8a|t1 1.347 0.098 13.713 0.000 1.347 1.347
## Cadri8a|t2 2.161 0.177 12.220 0.000 2.161 2.161
## Cadri8a|t3 2.740 0.329 8.326 0.000 2.740 2.740
## Cadri25a|t1 1.257 0.094 13.400 0.000 1.257 1.257
## Cadri25a|t2 2.249 0.192 11.707 0.000 2.249 2.249
## Cadri30a|t1 1.257 0.094 13.400 0.000 1.257 1.257
## Cadri30a|t2 2.024 0.157 12.925 0.000 2.024 2.024
## Cadri30a|t3 2.504 0.250 10.011 0.000 2.504 2.504
## Cadri34a|t1 1.328 0.097 13.656 0.000 1.328 1.328
## Cadri34a|t2 2.249 0.192 11.707 0.000 2.249 2.249
## Cadri34a|t3 2.740 0.329 8.326 0.000 2.740 2.740
## Cadri31a|t1 2.161 0.177 12.220 0.000 2.161 2.161
## Cadri31a|t2 2.504 0.250 10.011 0.000 2.504 2.504
## Cadri31a|t3 2.740 0.329 8.326 0.000 2.740 2.740
## Cadri33a|t1 1.871 0.138 13.536 0.000 1.871 1.871
## Cadri33a|t2 2.357 0.214 11.014 0.000 2.357 2.357
## Cadri33a|t3 2.740 0.329 8.326 0.000 2.740 2.740
## Cadri20a|t1 1.717 0.123 13.919 0.000 1.717 1.717
## Cadri20a|t2 2.161 0.177 12.220 0.000 2.161 2.161
## Cadri20a|t3 2.504 0.250 10.011 0.000 2.504 2.504
## Cadri21a|t1 1.089 0.087 12.530 0.000 1.089 1.089
## Cadri21a|t2 1.917 0.143 13.374 0.000 1.917 1.917
## Cadri21a|t3 2.357 0.214 11.014 0.000 2.357 2.357
## Cadri35a|t1 1.347 0.098 13.713 0.000 1.347 1.347
## Cadri35a|t2 2.161 0.177 12.220 0.000 2.161 2.161
## Cadri35a|t3 2.504 0.250 10.011 0.000 2.504 2.504
## Cadri2a|t1 1.386 0.100 13.817 0.000 1.386 1.386
## Cadri2a|t2 1.968 0.149 13.174 0.000 1.968 1.968
## Cadri2a|t3 2.249 0.192 11.707 0.000 2.249 2.249
## Cadri19a|t1 0.558 0.074 7.573 0.000 0.558 0.558
## Cadri19a|t2 1.257 0.094 13.400 0.000 1.257 1.257
## Cadri19a|t3 1.789 0.130 13.772 0.000 1.789 1.789
##
## Variances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .Cadri7a 0.445 0.445 0.445
## .Cadri9a 0.601 0.601 0.601
## .Cadri12a 0.404 0.404 0.404
## .Cadri17a 0.292 0.292 0.292
## .Cadri24a 0.533 0.533 0.533
## .Cadri28a 0.510 0.510 0.510
## .Cadri32a 0.452 0.452 0.452
## .Cadri8a 0.297 0.297 0.297
## .Cadri25a 0.386 0.386 0.386
## .Cadri30a 0.222 0.222 0.222
## .Cadri34a 0.322 0.322 0.322
## .Cadri31a 0.438 0.438 0.438
## .Cadri33a 0.003 0.003 0.003
## .Cadri20a 0.273 0.273 0.273
## .Cadri21a 0.246 0.246 0.246
## .Cadri35a 0.528 0.528 0.528
## .Cadri2a 0.645 0.645 0.645
## .Cadri19a 0.371 0.371 0.371
## .V_verbal 0.133 0.049 2.700 0.007 0.239 0.239
## .V_fisica 0.166 0.054 3.065 0.002 0.237 0.237
## .C_amenaz 0.027 0.047 0.570 0.568 0.048 0.048
## .V_relaci 0.351 0.094 3.748 0.000 0.483 0.483
## .V_sexual 0.230 0.086 2.659 0.008 0.648 0.648
## Violencia 0.537 0.086 6.261 0.000 1.000 1.000
##
## Scales y*:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## Cadri7a 1.000 1.000 1.000
## Cadri9a 1.000 1.000 1.000
## Cadri12a 1.000 1.000 1.000
## Cadri17a 1.000 1.000 1.000
## Cadri24a 1.000 1.000 1.000
## Cadri28a 1.000 1.000 1.000
## Cadri32a 1.000 1.000 1.000
## Cadri8a 1.000 1.000 1.000
## Cadri25a 1.000 1.000 1.000
## Cadri30a 1.000 1.000 1.000
## Cadri34a 1.000 1.000 1.000
## Cadri31a 1.000 1.000 1.000
## Cadri33a 1.000 1.000 1.000
## Cadri20a 1.000 1.000 1.000
## Cadri21a 1.000 1.000 1.000
## Cadri35a 1.000 1.000 1.000
## Cadri2a 1.000 1.000 1.000
## Cadri19a 1.000 1.000 1.000
## lhs op rhs mi epc sepc.lv sepc.all sepc.nox
## 388 V_verbal ~~ V_relaci 33.650 0.215 0.996 0.996 0.996
## 392 V_fisica ~~ V_relaci 19.289 -0.216 -0.893 -0.893 -0.893
## 391 V_fisica ~~ C_amenaz 16.734 0.192 2.864 2.864 2.864
## 368 Cadri31a ~~ Cadri35a 16.413 -0.252 -0.252 -0.523 -0.523
## 387 V_verbal ~~ C_amenaz 11.415 -0.155 -2.584 -2.584 -2.584
## 162 V_fisica =~ Cadri33a 10.635 1.327 1.113 1.113 1.113
## 351 Cadri30a ~~ Cadri31a 8.887 0.271 0.271 0.872 0.872
## 210 V_sexual =~ Cadri31a 8.517 0.577 0.344 0.344 0.344
## 259 Cadri9a ~~ Cadri31a 7.803 0.283 0.283 0.551 0.551
## 395 C_amenaz ~~ V_relaci 7.260 -0.135 -1.390 -1.390 -1.390
## 188 V_relaci =~ Cadri24a 6.584 0.292 0.249 0.249 0.249
## 306 Cadri24a ~~ Cadri2a 6.478 -0.215 -0.215 -0.367 -0.367
## 148 V_verbal =~ Cadri33a 6.296 -1.256 -0.936 -0.936 -0.936
## 195 V_relaci =~ Cadri31a 5.876 -0.422 -0.359 -0.359 -0.359
## 194 V_relaci =~ Cadri34a 5.607 -0.492 -0.420 -0.420 -0.420
## 369 Cadri31a ~~ Cadri2a 5.138 0.159 0.159 0.299 0.299
## 389 V_verbal ~~ V_sexual 4.492 -0.059 -0.339 -0.339 -0.339
## 304 Cadri24a ~~ Cadri21a 4.478 0.145 0.145 0.400 0.400
## 193 V_relaci =~ Cadri30a 4.303 -0.395 -0.337 -0.337 -0.337
## 152 V_verbal =~ Cadri2a 4.177 -0.779 -0.580 -0.580 -0.580
## For constructs with categorical indicators, the alpha and the average variance extracted are calculated from polychoric (polyserial) correlations, not from Pearson correlations.
## Higher-order factors were ignored.
## V_verbal V_fisica C_amenaz V_relaci V_sexual
## alpha 0.8869414 0.9004611 0.8562722 0.8443092 0.6416203
## omega 0.8207374 0.7758540 0.7471913 0.6761243 0.5205314
## omega2 0.8207374 0.7758540 0.7471913 0.6761243 0.5205314
## omega3 0.8262074 0.7763676 0.7471911 0.6737246 0.5205319
## avevar 0.5374648 0.6934609 0.7795125 0.6507830 0.4917860
## omegaL1 omegaL2 partialOmegaL1
## 0.8709181 0.9127616 0.9509889
semPlot::semPaths(fit08_b, whatLabels = "std", label.cex= 1.2,
edge.label.cex = 0.8, nCharEdges = 3,
nCharNodes = 8, sizeLat = 8, sizeLat2 = 3,
sizeMan = 8, sizeMan2 = 3, rotation = 2, intercepts = F,
thresholds = F, groups = "latents", pastel = TRUE,
exoVar = FALSE, edge.color = "black",
curvature = 2, mar = c(1, 6, 1, 6), residScale = 10,
manifests = rev(fit08_b@Data@ordered))
title("Modelo Factorial del CADRI \n Modelo 08 Segundo orden basado en modelo 04 fork")Este modelo de segundo orden está basado en el Modelo 07 que no considera al factor de conducta amenzante.
model09 <- "# Modelo de medición
V_verbal =~ Cadri7a + Cadri9a + Cadri12a + Cadri17a + Cadri24a + Cadri28a + Cadri32a
V_fis_am =~ Cadri8a + Cadri25a + Cadri30a + Cadri34a + Cadri31a + Cadri33a
V_relaci =~ Cadri20a + Cadri21a + Cadri35a
V_sexual =~ Cadri2a + Cadri19a
# Segundo orden
Violencia =~ V_fis_am + V_verbal + V_relaci + V_sexual"## Warning in lav_object_post_check(object): lavaan WARNING: some estimated lv
## variances are negative
## lavaan 0.6-6 ended normally after 99 iterations
##
## Estimator ML
## Optimization method NLMINB
## Number of free parameters 40
##
## Number of observations 326
##
## Model Test User Model:
## Standard Robust
## Test Statistic 354.028 208.290
## Degrees of freedom 131 131
## P-value (Chi-square) 0.000 0.000
## Scaling correction factor 1.700
## Yuan-Bentler correction (Mplus variant)
##
## Model Test Baseline Model:
##
## Test statistic 1844.236 940.536
## Degrees of freedom 153 153
## P-value 0.000 0.000
## Scaling correction factor 1.961
##
## User Model versus Baseline Model:
##
## Comparative Fit Index (CFI) 0.868 0.902
## Tucker-Lewis Index (TLI) 0.846 0.885
##
## Robust Comparative Fit Index (CFI) 0.915
## Robust Tucker-Lewis Index (TLI) 0.901
##
## Loglikelihood and Information Criteria:
##
## Loglikelihood user model (H0) -3315.327 -3315.327
## Scaling correction factor 7.061
## for the MLR correction
## Loglikelihood unrestricted model (H1) -3138.313 -3138.313
## Scaling correction factor 2.954
## for the MLR correction
##
## Akaike (AIC) 6710.654 6710.654
## Bayesian (BIC) 6862.130 6862.130
## Sample-size adjusted Bayesian (BIC) 6735.253 6735.253
##
## Root Mean Square Error of Approximation:
##
## RMSEA 0.072 0.043
## 90 Percent confidence interval - lower 0.063 0.034
## 90 Percent confidence interval - upper 0.081 0.051
## P-value RMSEA <= 0.05 0.000 0.933
##
## Robust RMSEA 0.055
## 90 Percent confidence interval - lower 0.041
## 90 Percent confidence interval - upper 0.069
##
## Standardized Root Mean Square Residual:
##
## SRMR 0.061 0.061
##
## Parameter Estimates:
##
## Standard errors Sandwich
## Information bread Observed
## Observed information based on Hessian
##
## Latent Variables:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## V_verbal =~
## Cadri7a 1.000 0.542 0.702
## Cadri9a 0.758 0.103 7.375 0.000 0.411 0.534
## Cadri12a 0.896 0.101 8.899 0.000 0.485 0.690
## Cadri17a 0.752 0.085 8.859 0.000 0.407 0.713
## Cadri24a 0.627 0.098 6.425 0.000 0.340 0.591
## Cadri28a 0.911 0.102 8.921 0.000 0.494 0.625
## Cadri32a 0.872 0.092 9.506 0.000 0.473 0.681
## V_fis_am =~
## Cadri8a 1.000 0.261 0.702
## Cadri25a 0.740 0.233 3.176 0.001 0.194 0.542
## Cadri30a 1.213 0.271 4.472 0.000 0.317 0.744
## Cadri34a 0.866 0.219 3.954 0.000 0.226 0.621
## Cadri31a 0.329 0.202 1.624 0.104 0.086 0.390
## Cadri33a 0.658 0.160 4.107 0.000 0.172 0.642
## V_relaci =~
## Cadri20a 1.000 0.196 0.578
## Cadri21a 1.774 0.440 4.034 0.000 0.348 0.717
## Cadri35a 1.132 0.390 2.903 0.004 0.222 0.568
## V_sexual =~
## Cadri2a 1.000 0.178 0.394
## Cadri19a 2.838 1.670 1.699 0.089 0.505 0.651
## Violencia =~
## V_fis_am 1.000 0.595 0.595
## V_verbal 3.621 1.569 2.307 0.021 1.039 1.039
## V_relaci 0.786 0.462 1.700 0.089 0.622 0.622
## V_sexual 0.464 0.310 1.498 0.134 0.406 0.406
##
## Variances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .Cadri7a 0.302 0.037 8.071 0.000 0.302 0.507
## .Cadri9a 0.423 0.049 8.585 0.000 0.423 0.715
## .Cadri12a 0.260 0.041 6.328 0.000 0.260 0.524
## .Cadri17a 0.160 0.024 6.696 0.000 0.160 0.491
## .Cadri24a 0.215 0.024 8.860 0.000 0.215 0.650
## .Cadri28a 0.380 0.044 8.584 0.000 0.380 0.609
## .Cadri32a 0.258 0.038 6.805 0.000 0.258 0.536
## .Cadri8a 0.070 0.014 4.924 0.000 0.070 0.508
## .Cadri25a 0.090 0.020 4.439 0.000 0.090 0.706
## .Cadri30a 0.081 0.031 2.664 0.008 0.081 0.447
## .Cadri34a 0.081 0.022 3.624 0.000 0.081 0.614
## .Cadri31a 0.041 0.024 1.701 0.089 0.041 0.848
## .Cadri33a 0.042 0.016 2.717 0.007 0.042 0.588
## .Cadri20a 0.077 0.029 2.626 0.009 0.077 0.666
## .Cadri21a 0.115 0.033 3.436 0.001 0.115 0.486
## .Cadri35a 0.104 0.031 3.373 0.001 0.104 0.678
## .Cadri2a 0.172 0.044 3.892 0.000 0.172 0.845
## .Cadri19a 0.346 0.171 2.026 0.043 0.346 0.576
## .V_verbal -0.023 0.089 -0.262 0.793 -0.079 -0.079
## .V_fis_am 0.044 0.021 2.096 0.036 0.646 0.646
## .V_relaci 0.024 0.016 1.521 0.128 0.613 0.613
## .V_sexual 0.026 0.018 1.488 0.137 0.835 0.835
## Violencia 0.024 0.017 1.408 0.159 1.000 1.000
fit09_b <- cfa(model = model09,
data = cadri_data,
ordered = TRUE,
estimator = "WLSMV",
mimic = "Mplus")## Warning in lav_model_vcov(lavmodel = lavmodel, lavsamplestats = lavsamplestats, : lavaan WARNING:
## The variance-covariance matrix of the estimated parameters (vcov)
## does not appear to be positive definite! The smallest eigenvalue
## (= -2.408315e-17) is smaller than zero. This may be a symptom that
## the model is not identified.
## lavaan 0.6-6 ended normally after 35 iterations
##
## Estimator DWLS
## Optimization method NLMINB
## Number of free parameters 75
##
## Number of observations 326
##
## Model Test User Model:
## Standard Robust
## Test Statistic 133.336 175.084
## Degrees of freedom 131 131
## P-value (Chi-square) 0.427 0.006
## Scaling correction factor 1.164
## Shift parameter 60.551
## simple second-order correction (WLSMV)
##
## Model Test Baseline Model:
##
## Test statistic 6023.208 2620.833
## Degrees of freedom 153 153
## P-value 0.000 0.000
## Scaling correction factor 2.379
##
## User Model versus Baseline Model:
##
## Comparative Fit Index (CFI) 1.000 0.982
## Tucker-Lewis Index (TLI) 1.000 0.979
##
## Robust Comparative Fit Index (CFI) NA
## Robust Tucker-Lewis Index (TLI) NA
##
## Root Mean Square Error of Approximation:
##
## RMSEA 0.007 0.032
## 90 Percent confidence interval - lower 0.000 0.018
## 90 Percent confidence interval - upper 0.028 0.044
## P-value RMSEA <= 0.05 1.000 0.995
##
## Robust RMSEA NA
## 90 Percent confidence interval - lower NA
## 90 Percent confidence interval - upper NA
##
## Standardized Root Mean Square Residual:
##
## SRMR 0.087 0.087
##
## Weighted Root Mean Square Residual:
##
## WRMR 0.805 0.805
##
## Parameter Estimates:
##
## Standard errors Robust.sem
## Information Expected
## Information saturated (h1) model Unstructured
##
## Latent Variables:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## V_verbal =~
## Cadri7a 1.000 0.744 0.744
## Cadri9a 0.848 0.071 11.944 0.000 0.631 0.631
## Cadri12a 1.041 0.065 16.058 0.000 0.775 0.775
## Cadri17a 1.130 0.069 16.363 0.000 0.841 0.841
## Cadri24a 0.916 0.061 14.954 0.000 0.682 0.682
## Cadri28a 0.937 0.068 13.840 0.000 0.697 0.697
## Cadri32a 0.996 0.062 16.023 0.000 0.741 0.741
## V_fis_am =~
## Cadri8a 1.000 0.829 0.829
## Cadri25a 0.934 0.073 12.816 0.000 0.774 0.774
## Cadri30a 1.047 0.082 12.745 0.000 0.868 0.868
## Cadri34a 0.980 0.075 13.027 0.000 0.813 0.813
## Cadri31a 0.946 0.113 8.370 0.000 0.784 0.784
## Cadri33a 1.133 0.086 13.221 0.000 0.940 0.940
## V_relaci =~
## Cadri20a 1.000 0.848 0.848
## Cadri21a 1.009 0.136 7.432 0.000 0.856 0.856
## Cadri35a 0.833 0.106 7.870 0.000 0.707 0.707
## V_sexual =~
## Cadri2a 1.000 0.595 0.595
## Cadri19a 1.336 0.313 4.263 0.000 0.794 0.794
## Violencia =~
## V_fis_am 1.000 0.809 0.809
## V_verbal 1.051 0.148 7.104 0.000 0.947 0.947
## V_relaci 0.914 0.155 5.900 0.000 0.723 0.723
## V_sexual 0.524 0.123 4.273 0.000 0.592 0.592
##
## Intercepts:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .Cadri7a 0.000 0.000 0.000
## .Cadri9a 0.000 0.000 0.000
## .Cadri12a 0.000 0.000 0.000
## .Cadri17a 0.000 0.000 0.000
## .Cadri24a 0.000 0.000 0.000
## .Cadri28a 0.000 0.000 0.000
## .Cadri32a 0.000 0.000 0.000
## .Cadri8a 0.000 0.000 0.000
## .Cadri25a 0.000 0.000 0.000
## .Cadri30a 0.000 0.000 0.000
## .Cadri34a 0.000 0.000 0.000
## .Cadri31a 0.000 0.000 0.000
## .Cadri33a 0.000 0.000 0.000
## .Cadri20a 0.000 0.000 0.000
## .Cadri21a 0.000 0.000 0.000
## .Cadri35a 0.000 0.000 0.000
## .Cadri2a 0.000 0.000 0.000
## .Cadri19a 0.000 0.000 0.000
## .V_verbal 0.000 0.000 0.000
## .V_fis_am 0.000 0.000 0.000
## .V_relaci 0.000 0.000 0.000
## .V_sexual 0.000 0.000 0.000
## Violencia 0.000 0.000 0.000
##
## Thresholds:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## Cadri7a|t1 0.178 0.070 2.539 0.011 0.178 0.178
## Cadri7a|t2 1.347 0.098 13.713 0.000 1.347 1.347
## Cadri7a|t3 1.717 0.123 13.919 0.000 1.717 1.717
## Cadri9a|t1 0.015 0.070 0.221 0.825 0.015 0.015
## Cadri9a|t2 1.177 0.090 13.029 0.000 1.177 1.177
## Cadri9a|t3 1.871 0.138 13.536 0.000 1.871 1.871
## Cadri12a|t1 0.549 0.074 7.465 0.000 0.549 0.549
## Cadri12a|t2 1.495 0.107 14.000 0.000 1.495 1.495
## Cadri12a|t3 1.871 0.138 13.536 0.000 1.871 1.871
## Cadri17a|t1 0.844 0.079 10.623 0.000 0.844 0.844
## Cadri17a|t2 1.654 0.118 14.003 0.000 1.654 1.654
## Cadri17a|t3 2.357 0.214 11.014 0.000 2.357 2.357
## Cadri24a|t1 0.445 0.072 6.162 0.000 0.445 0.445
## Cadri24a|t2 1.871 0.138 13.536 0.000 1.871 1.871
## Cadri24a|t3 2.357 0.214 11.014 0.000 2.357 2.357
## Cadri28a|t1 0.462 0.072 6.380 0.000 0.462 0.462
## Cadri28a|t2 1.177 0.090 13.029 0.000 1.177 1.177
## Cadri28a|t3 1.828 0.134 13.667 0.000 1.828 1.828
## Cadri32a|t1 0.622 0.075 8.324 0.000 0.622 0.622
## Cadri32a|t2 1.569 0.112 14.040 0.000 1.569 1.569
## Cadri32a|t3 1.828 0.134 13.667 0.000 1.828 1.828
## Cadri8a|t1 1.347 0.098 13.713 0.000 1.347 1.347
## Cadri8a|t2 2.161 0.177 12.220 0.000 2.161 2.161
## Cadri8a|t3 2.740 0.329 8.326 0.000 2.740 2.740
## Cadri25a|t1 1.257 0.094 13.400 0.000 1.257 1.257
## Cadri25a|t2 2.249 0.192 11.707 0.000 2.249 2.249
## Cadri30a|t1 1.257 0.094 13.400 0.000 1.257 1.257
## Cadri30a|t2 2.024 0.157 12.925 0.000 2.024 2.024
## Cadri30a|t3 2.504 0.250 10.011 0.000 2.504 2.504
## Cadri34a|t1 1.328 0.097 13.656 0.000 1.328 1.328
## Cadri34a|t2 2.249 0.192 11.707 0.000 2.249 2.249
## Cadri34a|t3 2.740 0.329 8.326 0.000 2.740 2.740
## Cadri31a|t1 2.161 0.177 12.220 0.000 2.161 2.161
## Cadri31a|t2 2.504 0.250 10.011 0.000 2.504 2.504
## Cadri31a|t3 2.740 0.329 8.326 0.000 2.740 2.740
## Cadri33a|t1 1.871 0.138 13.536 0.000 1.871 1.871
## Cadri33a|t2 2.357 0.214 11.014 0.000 2.357 2.357
## Cadri33a|t3 2.740 0.329 8.326 0.000 2.740 2.740
## Cadri20a|t1 1.717 0.123 13.919 0.000 1.717 1.717
## Cadri20a|t2 2.161 0.177 12.220 0.000 2.161 2.161
## Cadri20a|t3 2.504 0.250 10.011 0.000 2.504 2.504
## Cadri21a|t1 1.089 0.087 12.530 0.000 1.089 1.089
## Cadri21a|t2 1.917 0.143 13.374 0.000 1.917 1.917
## Cadri21a|t3 2.357 0.214 11.014 0.000 2.357 2.357
## Cadri35a|t1 1.347 0.098 13.713 0.000 1.347 1.347
## Cadri35a|t2 2.161 0.177 12.220 0.000 2.161 2.161
## Cadri35a|t3 2.504 0.250 10.011 0.000 2.504 2.504
## Cadri2a|t1 1.386 0.100 13.817 0.000 1.386 1.386
## Cadri2a|t2 1.968 0.149 13.174 0.000 1.968 1.968
## Cadri2a|t3 2.249 0.192 11.707 0.000 2.249 2.249
## Cadri19a|t1 0.558 0.074 7.573 0.000 0.558 0.558
## Cadri19a|t2 1.257 0.094 13.400 0.000 1.257 1.257
## Cadri19a|t3 1.789 0.130 13.772 0.000 1.789 1.789
##
## Variances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .Cadri7a 0.446 0.446 0.446
## .Cadri9a 0.601 0.601 0.601
## .Cadri12a 0.400 0.400 0.400
## .Cadri17a 0.292 0.292 0.292
## .Cadri24a 0.535 0.535 0.535
## .Cadri28a 0.514 0.514 0.514
## .Cadri32a 0.451 0.451 0.451
## .Cadri8a 0.312 0.312 0.312
## .Cadri25a 0.400 0.400 0.400
## .Cadri30a 0.246 0.246 0.246
## .Cadri34a 0.340 0.340 0.340
## .Cadri31a 0.385 0.385 0.385
## .Cadri33a 0.117 0.117 0.117
## .Cadri20a 0.281 0.281 0.281
## .Cadri21a 0.268 0.268 0.268
## .Cadri35a 0.501 0.501 0.501
## .Cadri2a 0.647 0.647 0.647
## .Cadri19a 0.369 0.369 0.369
## .V_verbal 0.057 0.065 0.882 0.378 0.103 0.103
## .V_fis_am 0.238 0.063 3.751 0.000 0.346 0.346
## .V_relaci 0.343 0.093 3.701 0.000 0.477 0.477
## .V_sexual 0.230 0.087 2.642 0.008 0.650 0.650
## Violencia 0.450 0.084 5.386 0.000 1.000 1.000
##
## Scales y*:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## Cadri7a 1.000 1.000 1.000
## Cadri9a 1.000 1.000 1.000
## Cadri12a 1.000 1.000 1.000
## Cadri17a 1.000 1.000 1.000
## Cadri24a 1.000 1.000 1.000
## Cadri28a 1.000 1.000 1.000
## Cadri32a 1.000 1.000 1.000
## Cadri8a 1.000 1.000 1.000
## Cadri25a 1.000 1.000 1.000
## Cadri30a 1.000 1.000 1.000
## Cadri34a 1.000 1.000 1.000
## Cadri31a 1.000 1.000 1.000
## Cadri33a 1.000 1.000 1.000
## Cadri20a 1.000 1.000 1.000
## Cadri21a 1.000 1.000 1.000
## Cadri35a 1.000 1.000 1.000
## Cadri2a 1.000 1.000 1.000
## Cadri19a 1.000 1.000 1.000
## For constructs with categorical indicators, the alpha and the average variance extracted are calculated from polychoric (polyserial) correlations, not from Pearson correlations.
## Higher-order factors were ignored.
## V_verbal V_fis_am V_relaci V_sexual
## alpha 0.8869414 0.9257101 0.8443092 0.6416203
## omega 0.8206861 0.8163989 0.6724028 0.5218421
## omega2 0.8206861 0.8163989 0.6724028 0.5218421
## omega3 0.8259776 0.8204771 0.6709403 0.5218420
## avevar 0.5374292 0.7000276 0.6501830 0.4923251
## omegaL1 omegaL2 partialOmegaL1
## 0.8537566 0.8632906 0.9486812
semPlot::semPaths(fit09_b, whatLabels = "std", label.cex= 1.2,
edge.label.cex = 0.8, nCharEdges = 3,
nCharNodes = 8, sizeLat = 8, sizeLat2 = 3,
sizeMan = 8, sizeMan2 = 3, rotation = 2, intercepts = F,
thresholds = F, groups = "latents", pastel = TRUE,
exoVar = FALSE, edge.color = "black",
curvature = 2, mar = c(1, 6, 1, 6), residScale = 10,
manifests = rev(fit09_b@Data@ordered))
title("Modelo Factorial del CADRI \n Modelo 09 Segundo orden basado en modelo 07")Mediante el uso de una función personalizada, se realiza la comparación de los índices de ajustes de todos los modelos, tanto por MLR como por WLSMV.
MLRcompare_fit_mlr <- bind_rows(
glance.lavaan.fix(fit01_a),
glance.lavaan.fix(fit02_a),
glance.lavaan.fix(fit03_a),
glance.lavaan.fix(fit04_a),
glance.lavaan.fix(fit04_a_fork),
glance.lavaan.fix(fit05_a),
glance.lavaan.fix(fit06_a),
glance.lavaan.fix(fit07_a),
glance.lavaan.fix(fit08_a),
glance.lavaan.fix(fit09_a),
.id = "Modelo"
) %>%
mutate(Modelo = fct_recode(Modelo,
"Modelo 01" = "1",
"Modelo 02" = "2",
"Modelo 03" = "3",
"Modelo 04" = "4",
"Modelo 04 fork" = "5",
"Modelo 05" = "6",
"Modelo 06" = "7",
"Modelo 07" = "8",
"Modelo 08" = "9",
"Modelo 09" = "10")) %>%
mutate_if(is.numeric, round, 3)WLSMVcompare_fit_wlsmv <- bind_rows(
glance.lavaan.fix(fit01_b),
glance.lavaan.fix(fit02_b),
glance.lavaan.fix(fit03_b),
glance.lavaan.fix(fit04_b),
glance.lavaan.fix(fit04_b_fork),
glance.lavaan.fix(fit05_b),
glance.lavaan.fix(fit06_b),
glance.lavaan.fix(fit07_b),
glance.lavaan.fix(fit08_b),
glance.lavaan.fix(fit09_b),
.id = "Modelo"
) %>%
mutate(Modelo = fct_recode(Modelo,
"Modelo 01" = "1",
"Modelo 02" = "2",
"Modelo 03" = "3",
"Modelo 04" = "4",
"Modelo 04 fork" = "5",
"Modelo 05" = "6",
"Modelo 06" = "7",
"Modelo 07" = "8",
"Modelo 08" = "9",
"Modelo 09" = "10")) %>%
mutate_if(is.numeric, round, 3)